The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 153, in compute
compute_split_names_from_info_response(
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 125, in compute_split_names_from_info_response
config_info_response = get_previous_step_or_raise(kind="config-info", dataset=dataset, config=config)
File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 591, in get_previous_step_or_raise
raise CachedArtifactError(
libcommon.simple_cache.CachedArtifactError: The previous step failed.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 499, in get_dataset_config_info
for split_generator in builder._split_generators(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 88, in _split_generators
raise ValueError(
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 572, in get_dataset_split_names
info = get_dataset_config_info(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 504, 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.
Wildfires - CEMS
The dataset includes annotations for burned area delineation and land cover segmentation, with a focus on European soil. The dataset is curated from various sources, including the Copernicus European Monitoring System (EMS) and Sentinel-2 feeds.
- Repository: https://github.com/links-ads/burned-area-seg
- Paper: https://paperswithcode.com/paper/robust-burned-area-delineation-through
Dataset Preparation
The dataset has been compressed into segmentented tarballs for ease of use within Git LFS (that is, tar > gzip > split). To revert the process into files and directories follow these steps:
$ git clone https://huggingface.co/datasets/links-ads/wildfires-cems
$ cd wildfires-ems
# revert the multipart compression: merge first, then untar
$ cat data/train/train.tar.* | tar -xzvf - -i
$ cat data/test/test.tar.* | tar -xzvf - -i
$ cat data/val/val.tar.* | tar -xzvf - -i
It is very likely that the extracted files will retain the internal directory structure, making the train/val/test directories useless.
Adapt the output structure as you see fit, the original structure is shown below.
Dataset Structure
The main dataset used in the paper comprises the following inputs:
| Suffix | Data Type | Description | Format |
|---|---|---|---|
| S2L2A | Sentinel-2 Image | L2A data with 12 channels in reflectance/10k format | GeoTIFF (.tif) |
| DEL | Delineation Map | Binary map indicating burned areas as uint8 values (0 or 1) | GeoTIFF (.tif) |
| GRA | Grading Map | Grading information (if available) with uint8 values ranging from 0 to 4 | GeoTIFF (.tif) |
| ESA_LC | Land Cover Map | ESA WorldCover 2020 land cover classes as uint8 values | GeoTIFF (.tif) |
| CM | Cloud Cover Map | Cloud cover mask, uint8 values generated using CloudSen12 (0 or 1) | GeoTIFF (.tif) |
Additionally, the dataset also contains two land cover variants, the ESRI Annual Land Cover (9 categories) and the static variant (10 categories), not used in this study.
The dataset already provides a train / val / test split for convenience, however the inner structure of each group is the same.
The folders are structured as follows:
train/val/test/
├── EMSR230/
│ ├── AOI01/
│ │ ├── EMSR230_AOI01_01/
│ │ │ ├── EMSR230_AOI01_01_CM.png
│ │ │ ├── EMSR230_AOI01_01_CM.tif
│ │ │ ├── EMSR230_AOI01_01_DEL.png
│ │ │ ├── EMSR230_AOI01_01_DEL.tif
│ │ │ ├── EMSR230_AOI01_01_ESA_LC.png
│ │ │ ├── EMSR230_AOI01_01_ESA_LC.tif
│ │ │ ├── EMSR230_AOI01_01_GRA.png
│ │ │ ├── EMSR230_AOI01_01_GRA.tif
│ │ │ ├── EMSR230_AOI01_01_S2L2A.json -> metadata information
│ │ │ ├── EMSR230_AOI01_01_S2L2A.png -> RGB visualization
│ │ │ └── EMSR230_AOI01_01_S2L2A.tif
│ │ │ └── ...
│ │ ├── EMSR230_AOI01_02/
│ │ │ └── ...
│ │ ├── ...
│ ├── AOI02/
│ │ └── ...
│ ├── ...
├── EMSR231/
│ ├── ...
├── ...
Source Data
- Activations are directly derived from Copernicus EMS (CEMS): https://emergency.copernicus.eu/mapping/list-of-activations-rapid
- Sentinel-2 and LC images are downloaded from Microsoft Planetary Computer, using the AoI provided by CEMS.
- DEL and GRA maps represent the rasterized version of the delineation/grading products provided by the Copernicus service.
Licensing Information
CC-BY-4.0 https://creativecommons.org/licenses/by/4.0/
Citation Information
@inproceedings{arnaudo2023burned,
title={Robust Burned Area Delineation through Multitask Learning},
author={Arnaudo, Edoardo and Barco, Luca and Merlo, Matteo and Rossi, Claudio},
booktitle={Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year={2023}
}
Contributions
- Luca Barco (luca.barco@linksfoundation.com)
- Edoardo Arnaudo (edoardo.arnaudo@polito.it | linksfoundation.com)
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