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in Data Studio
Dubai Aerial Semantic Segmentation Dataset
About the Dataset
Semantic segmentation of aerial imagery over Dubai, United Arab Emirates (UAE), into six land cover classes.
Context
Humans in the Loop is publishing this open-access dataset, created in collaboration with the Mohammed Bin Rashid Space Center (MBRSC) in Dubai, UAE.
The dataset aims to support machine learning and computer vision tasks in urban analysis, environmental monitoring, and remote sensing.
Semantic Classes and Color Codes
| Class | Hex Color Code |
|---|---|
| Building | #3C1098 |
| Land (Unpaved Area) | #8429F6 |
| Road | #6EC1E4 |
| Vegetation | #FEDD3A |
| Water | #E2A929 |
| Unlabeled | #9B9B9B |
Acknowledgements
The images were segmented by trainees of the Roia Foundation in Syria under the supervision of Humans in the Loop.
License
This dataset is licensed under CC0 1.0 Universal (Public Domain Dedication) — free to use for any purpose.
- Downloads last month
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Source
: Aerial imagery obtained from MBRSC satellites
Annotations
: Pixel-wise semantic segmentation
Total images
: 72
Grouping
: Images are organized into 6 larger tiles
Classes
: 6 semantic categories
Size of downloaded dataset files:
33.5 MB
Size of the auto-converted Parquet files:
32.6 MB
Number of rows:
144