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---
license: openrail
task_categories:
- image-segmentation
pretty_name: California Burned Areas
size_categories:
- n<1K
---
# California Burned Areas Dataset

## 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

### 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.

### Data Fields

In each HDF5 file, you can find post-fire, pre-fire images and binary masks. The file is structured in this way:

```bash
β”œβ”€β”€ foldn
β”‚   β”œβ”€β”€ uid0
β”‚   β”‚   β”œβ”€β”€ pre_fire
β”‚   β”‚   β”œβ”€β”€ post_fire
β”‚   β”‚   β”œβ”€β”€ mask 
β”‚   β”œβ”€β”€ uid1
β”‚       β”œβ”€β”€ post_fire
β”‚       β”œβ”€β”€ mask
β”‚  
β”œβ”€β”€ foldm
    β”œβ”€β”€ uid2
    β”‚   β”œβ”€β”€ post_fire
    β”‚   β”œβ”€β”€ mask 
    β”œβ”€β”€ uid3
        β”œβ”€β”€ pre_fire
        β”œβ”€β”€ post_fire
        β”œβ”€β”€ mask
...
```

where `foldn` and `foldm` are fold names and `uidn` is a unique identifier for the wilfire.

### 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

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

[More Information Needed]