Update README.md

README.md

@@ -14,11 +14,7 @@ tags:
 
 ## Dataset Description
 
-- **Homepage:** 
-- **Repository:** 
 - **Paper:** 
-- **Leaderboard:** 
-- **Point of Contact:** 
 
 ### Dataset Summary
 
@@ -35,16 +31,19 @@ We opted to use HDF5 to grant better portability and lower file size than GeoTIF
 
 ### Dataset opening
 
-Dataset was compressed using `h5py` and BZip2 from `hdf5plugin`. **WARNING: `hdf5plugin` is necessary to extract data**.
+The 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.
+Pre-patched version is provided with matrices of size 512x512xC, too. In this case, only mask with at least one positive pixel is present.
+
+You can find two versions of the dataset: _raw_ (without any transformation) and _normalized_ (with data normalized in the range 0-255). 
+Our suggestion is to use the _raw_ version to have the possibility to apply any wanted pre-processing step.
 
 ### 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:
+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
@@ -67,7 +66,7 @@ In each standard HDF5 file, you can find post-fire, pre-fire images and binary m
 ...
 ```
 
-where `foldn` and `foldm` are fold names and `uidn` is a unique identifier for the wilfire.
+where `foldn` and `foldm` are fold names and `uidn` is a unique identifier for the wildfire.
 
 For the pre-patched version, the structure is:
 ```bash
@@ -81,62 +80,31 @@ root
 |
 ...
 ```
-the fold name is stored as attribute.
+the fold name is stored as an attribute.
 
 ### Data Splits
 
-There are 5 random splits whose names are: 0, 1, 2, 3 and 4.
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed]
+There are 5 random splits whose names are: 0, 1, 2, 3, and 4.
 
 ### 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]
+If you plan to use this dataset in your work please give the credit to Sentinel-2 mission and the California Department of Forestry and Fire Protection and cite using this BibTex:
+```
+@article{
+  title={CaBuAr: California Burned Areas dataset for delineation},
+  author={Rege Cambrin, Daniele; Colomba, Luca; Garza, Paolo},
+  journal={IEEE Geoscience and Remote Sensing Magazine},
+  doi={10.1109/MGRS.2023.3292467},
+  year={2023} 
+}
+```