Update README.md

README.md

@@ -1,3 +1,96 @@
 ---
 license: cc-by-4.0
+task_categories:
+- image-segmentation
+- image-classification
+language:
+- en
+tags:
+- semantic segmentation
+- remote sensing
+- sentinel
+- wildfire
+pretty_name: Wildfires - CEMS
+size_categories:
+- 1K<n<10K
 ---
+# 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:** Coming soon
+---------
+![Dataset sample](assets/sample.png)
+
+## 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](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/](https://creativecommons.org/licenses/by/4.0/)
+
+### Citation Information
+
+```bibtex
+@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)