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--- |
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license: openrail |
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task_categories: |
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- image-segmentation |
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pretty_name: California Burned Areas |
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size_categories: |
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- n<1K |
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tags: |
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- climate |
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--- |
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# California Burned Areas Dataset |
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**Working on adding more data** |
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## Dataset Description |
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- **Homepage:** |
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- **Repository:** |
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- **Paper:** |
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- **Leaderboard:** |
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- **Point of Contact:** |
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### Dataset Summary |
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This dataset contains images from Sentinel-2 satellites taken before and after a wildfire. |
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The ground truth masks are provided by the California Department of Forestry and Fire Protection and they are mapped on the images. |
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### Supported Tasks |
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The dataset is designed to do binary semantic segmentation of burned vs unburned areas. |
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## Dataset Structure |
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We opted to use HDF5 to grant better portability and lower file size than GeoTIFF. |
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### Dataset opening |
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Dataset was compressed using `h5py` and BZip2 from `hdf5plugin`. **WARNING: `hdf5plugin` is necessary to extract data**. |
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### Data Instances |
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Each matrix has a shape of 5490x5490xC, where C is 12 for pre-fire and post-fire images, while it is 0 for binary masks. |
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Pre-patched version with matrices of size 512x512xC version are provided, too. In this case only mask with at least one positive pixel are present. |
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### Data Fields |
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In each standard HDF5 file, you can find post-fire, pre-fire images and binary masks. The file is structured in this way: |
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```bash |
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├── foldn |
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│ ├── uid0 |
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│ │ ├── pre_fire |
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│ │ ├── post_fire |
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│ │ ├── mask |
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│ ├── uid1 |
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│ ├── post_fire |
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│ ├── mask |
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│ |
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├── foldm |
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├── uid2 |
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│ ├── post_fire |
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│ ├── mask |
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├── uid3 |
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├── pre_fire |
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├── post_fire |
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├── mask |
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... |
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``` |
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where `foldn` and `foldm` are fold names and `uidn` is a unique identifier for the wilfire. |
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For the pre-patched version, the structure is: |
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```bash |
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root |
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|-- uid0_x: {post_fire, pre_fire, mask} |
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|-- uid0_y: {post_fire, pre_fire, mask} |
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|-- uid1_x: {post_fire, mask} |
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... |
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``` |
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the fold name is stored as attribute. |
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### Data Splits |
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There are 5 random splits whose names are: 0, 1, 2, 3 and 4. |
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## Dataset Creation |
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### Curation Rationale |
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[More Information Needed] |
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### Source Data |
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#### Initial Data Collection and Normalization |
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Data are collected directly from Copernicus Open Access Hub through the API. The band files are aggregated into one single matrix. |
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### Annotations |
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#### Annotation process |
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[More Information Needed] |
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#### Who are the annotators? |
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[More Information Needed] |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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[More Information Needed] |
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### Discussion of Biases |
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[More Information Needed] |
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### Other Known Limitations |
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[More Information Needed] |
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## Additional Information |
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### Dataset Curators |
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[More Information Needed] |
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### Licensing Information |
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This work is under OpenRAIL license. |
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### Citation Information |
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If you plan to use this dataset in your work please cite using the DOI and giving the credit to Sentinel-2 mission and California Department of Forestry and Fire Protection. |
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### Contributions |
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[More Information Needed] |
