ibm-nasa-geospatial/Prithvi-100M-burn-scar
Updated
•
27
Search is not available for this dataset
The dataset viewer is not available for this split.
The info cannot be fetched for the config 'hls_burn_scars' of the dataset.
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.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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}
}
- Downloads last month
- 896
Homepage: https://huggingface.co/datasets/nasa-impact/hls_burn_scars
Homepage: https://huggingface.co/datasets/nasa-impact/hls_burn_scars
Point of Contact: Dr. Christopher Phillips ([email protected])
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