Datasets:

aialliance
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treesatai

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train

The dataset viewer is not available for this split.

Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.

Error code:   FeaturesError
Exception:    ValueError
Message:      Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/aialliance/treesatai@ea3c6b6e515bd3a7172e70500d3e9f3751e940d7/treesatai_stats_satmae.json.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3422, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2187, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2391, in iter
                  for key, example in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1882, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1904, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 499, in _iter_arrow
                  for key, pa_table in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 346, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/json/json.py", line 186, in _generate_tables
                  raise ValueError(
              ValueError: Failed to convert pandas DataFrame to Arrow Table from file hf://datasets/aialliance/treesatai@ea3c6b6e515bd3a7172e70500d3e9f3751e940d7/treesatai_stats_satmae.json.

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GeoBench-2 Dataset License Attribution

Dataset Name: m-TreeSatAI
Original Dataset Name: TreeSatAI
Original Source: https://zenodo.org/records/6780578 Related Publication(s): https://doi.org/10.5194/essd-15-681-2023

Licensing

Annotation License: CC BY 4.0 (as declared in the paper)
Image License:
- Aerial imagery (NLF / German state forestry): CC BY 4.0 (per the dataset’s license)
- Sentinel-1 / Sentinel-2: Copernicus open access (public domain / free use)
Declared By Original Provider: Zenodo record (https://zenodo.org/records/6598391) and the ESSD article stating “© Author(s) 2023. This work is distributed under the Creative Commons Attribution 4.0 License.”

Redistribution Status in GeoBench-2
This dataset is redistributed under the same license terms as declared by the original providers.
ServiceNow Research, IBM Research, TUM, and AI Alliance do not claim ownership or grant new rights beyond those already specified.

Attribution Requirements

When using this dataset (directly or through GeoBench-2), please cite the original dataset creators and reference both the dataset page and publication:

Ahlswede, S., Schulz, C., Gava, C., Helber, P., Bischke, B., Förster, M., Arias, F., Hees, J., Demir, B., & Kleinschmit, B.
“TreeSatAI Benchmark Archive: a multi-sensor, multi-label dataset for tree species classification in remote sensing.” Earth System Science Data, 15, 681–695, 2023.
Dataset archive: https://zenodo.org/records/6780578

License Disclaimer & Takedown Policy

GEO-Bench-2 redistributes transformed versions of publicly available datasets for research and benchmarking purposes. Each dataset included here is redistributed under the same license terms designated by its original licensor.

No New Rights Created: ServiceNow Research, IBM Research, TUM, and AI Alliance do not claim ownership over these datasets and do not grant any new rights beyond those already specified by the original licensors.

Attribution: All credit remains with the original dataset creators and providers. Each dataset is accompanied by license and attribution information pointing to the original source.

Disclaimer of Responsibility: The consortium partners act only as redistributors. We do not independently verify the accuracy of the license terms supplied by original dataset providers and disclaim liability for any errors, omissions, or misattributions in those designations.

Takedown Procedure: If you are a rights holder and believe that a dataset has been misattributed, incorrectly licensed, or should not be redistributed in this form, please contact Paolo Fraccaro ([email protected]) and Alexandre Lacoste ([email protected]). We will promptly review and, if necessary, remove or modify access to the dataset.

By accessing or using GEO-Bench-2, you agree to comply with the original dataset licenses and acknowledge that the responsibility for verifying appropriate use lies with the end-user.

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