Datasets:

ibm-nasa-geospatial
/

hls_burn_scars

Error code:   InfoError
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 434, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                File "/tmp/modules-cache/datasets_modules/datasets/ibm-nasa-geospatial--hls_burn_scars/61edc94bab1a179fe9a10b03d9ee90b7b2d028f2b548637beb4a28db277e133a/hls_burn_scars.py", line 57, in _split_generators
                  data_dirs = dl_manager.download_and_extract(urls)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1063, in download_and_extract
                  return self.extract(self.download(url_or_urls))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1015, in extract
                  urlpaths = map_nested(self._extract, url_or_urls, map_tuple=True)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 464, in map_nested
                  mapped = [
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 465, in <listcomp>
                  _single_map_nested((function, obj, types, None, True, None))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/py_utils.py", line 367, in _single_map_nested
                  return function(data_struct)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/download/streaming_download_manager.py", line 1025, in _extract
                  raise NotImplementedError(
              NotImplementedError: Extraction protocol for TAR archives like 'https://huggingface.co./datasets/ibm-nasa-geospatial/hls_burn_scars/resolve/main/hls_burn_scars.tar.gz' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead.
              
              Example usage:
              
              	url = dl_manager.download(url)
              	tar_archive_iterator = dl_manager.iter_archive(url)
              
              	for filename, file in tar_archive_iterator:
              		...
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows_from_streaming.py", line 140, in compute_first_rows_response
                  info = get_dataset_config_info(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 439, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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Dataset Card for HLS Burn Scar Scenes

Dataset Summary

This dataset contains Harmonized Landsat and Sentinel-2 imagery of burn scars and the associated masks for the years 2018-2021 over the contiguous United States. There are 804 512x512 scenes. Its primary purpose is for training geospatial machine learning models.

Dataset Structure

TIFF Metadata

Each tiff file contains a 512x512 pixel tiff file. Scenes contain six bands, and masks have one band. For satellite scenes, each band has already been converted to reflectance.

Band Order

For scenes: Channel, Name, HLS S30 Band number
1, Blue, B02
2, Green, B03
3, Red, B04
4, NIR, B8A
5, SW 1, B11
6, SW 2, B12

Masks are a single band with values:
1 = Burn scar
0 = Not burned
-1 = Missing data

Class Distribution

Burn Scar - 11%
Not burned - 88%
No Data - 1%

Data Splits

The 804 files have been randomly split into training (2/3) and validation (1/3) directories, each containing the masks, scenes, and index files.

Dataset Creation

After co-locating the shapefile and HLS scene, the 512x512 chip was formed by taking a window with the burn scar in the center. Burn scars near the edges of HLS tiles are offset from the center.
Images were manually filtered for cloud cover and missing data to provide as clean a scene as possible, and burn scar presence was also manually verified.

Source Data

Imagery are from V1.4 of HLS. A full description and access to HLS may be found at https://hls.gsfc.nasa.gov/

The data were from shapefiles maintained by the Monitoring Trends in Burn Severity (MTBS) group. The original data may be found at:
https://mtbs.gov/

Citation

If this dataset helped your research, please cite HLS Burn Scars in your publications. Here is an example BibTeX entry:

@software{HLS_Foundation_2023,
    author = {Phillips, Christopher and Roy, Sujit and Ankur, Kumar and Ramachandran, Rahul},
    doi    = {10.57967/hf/0956},
    month  = aug,
    title  = {{HLS Foundation Burnscars Dataset}},
    url    = {https://huggingface.co./ibm-nasa-geospatial/hls_burn_scars},
    year   = {2023}
}

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Homepage: https://huggingface.co./datasets/nasa-impact/hls_burn_scars

Point of Contact: Dr. Christopher Phillips ([email protected])

Size of downloaded dataset files:

2.65 GB

Size of the auto-converted Parquet files:

5.65 GB

Number of rows:

1,068

Models trained or fine-tuned on ibm-nasa-geospatial/hls_burn_scars

ibm-nasa-geospatial/Prithvi-100M-burn-scar

Updated Nov 6, 2023 • 27