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