metadata
license: cc-by-nc-4.0
pipeline_tag: image-segmentation
tags:
- remote sensing
- sentinel2
- landsat
- floods
WorldFloodsv2 dataset
This repository contains the WorldFloodsv2 dataset released with the publication:
E. Portalés-Julià, G. Mateo-García, C. Purcell, and L. Gómez-Chova Global flood extent segmentation in optical satellite images. Scientific Reports 13, 20316 (2023). DOI: 10.1038/s41598-023-47595-7.
The WorldFloodsv2 database contains 509 pairs of Sentinel-2 images and flood segmentation masks. Splitted in train, val and test sets. It requires approximately 76GB of hard-disk storage.
Download the dataset
huggingface-cli download --cache-dir /path/to/cachedir --local-dir /path/to/localdir/WorldFloodsv2 --repo-type dataset isp-uv-es/WorldFloodsv2
Explore the dataset
The following ml4floods tutorials may help you explore and use this dataset:
- The exploring WorldFloodsv2 tutorial shows how to process the dataset and plot the images and masks.
- The WorldFloodsV2 torch dataset tutorial shows how to load the dataset with pytorch data loaders.
Licence
The WorldFloods database and all pre-trained models are released under a Creative Commons non-commercial licence
Cite
If you find this work useful, please cite:
@article{portales-julia_global_2023,
title = {Global flood extent segmentation in optical satellite images},
volume = {13},
issn = {2045-2322},
doi = {10.1038/s41598-023-47595-7},
number = {1},
urldate = {2023-11-30},
journal = {Scientific Reports},
author = {Portalés-Julià, Enrique and Mateo-García, Gonzalo and Purcell, Cormac and Gómez-Chova, Luis},
month = nov,
year = {2023},
pages = {20316},
}