---
license: cc-by-nc-4.0
---
This repository contains the trained models of the publication:
Portalés-Julià, Enrique and Mateo-García, Gonzalo and Gómez-Chova, Luis, [**Understanding Flood Detection Models Across Sentinel-1 and Sentinel-2 Modalities and Benchmark Datasets.**](https://www.sciencedirect.com/science/article/pii/S003442572500286X#bib1), published in Remote Sensing of Environment.
We include the trained models:
* **sm_unet_s2** Model trained on the Sentinel-2 L1C bands `["B02", "B03", "B04", "B08", "B11", "B12"]` from the S1S2Water and WorldFloods datasets.
* **sm_unet_s1** Model trained on the Sentinel-1 GRD data (`[VV, VH]` channels) from the S1S2Water and Kuro Siwo datasets.
* **mm_unet_s1s2** Dual stream with modality token model, trained on the S1S2Water (Sentinel-1 GRD and Sentinel-2 L1C data), WorldFloods (Sentinel-2 L1C) and Kuro Siwo Sentinel-1 GRD data.
In order to run any of these models in Sentinel-1 and/or Sentinel-2 data see the tutorial [*Run model*](https://github.com/kipoju/udl4fl/blob/main/notebooks/run_in_gee_image.ipynb) in the [udl4fl](https://github.com/kipoju/udl4fl) package.
If you find this work useful please cite:
```
@article{PORTALESJULIA2025114882,
title = {Understanding flood detection models across Sentinel-1 and Sentinel-2 modalities and benchmark datasets},
journal = {Remote Sensing of Environment},
volume = {328},
pages = {114882},
year = {2025},
issn = {0034-4257},
doi = {https://doi.org/10.1016/j.rse.2025.114882},
url = {https://www.sciencedirect.com/science/article/pii/S003442572500286X},
author = {Enrique Portalés-Julià and Gonzalo Mateo-García and Luis Gómez-Chova},
keywords = {Flood detection, Deep learning, Multimodal fusion, Multispectral, SAR, Sentinel-1, Sentinel-2},
}
```
## Licence
All pre-trained models in this repository are released under a [Creative Commons non-commercial licence](https://creativecommons.org/licenses/by-nc/4.0/legalcode.txt)
The `udl4fl` python package is published under a [GNU Lesser GPL v3 licence](https://www.gnu.org/licenses/lgpl-3.0.en.html)
## Acknowledgments
This research has been supported by the DEEPCLOUD project (PID2019-109026RB-I00, University of Valencia) funded by the Spanish Ministry of Science and Innovation (MCIN/AEI/10.13039/501100011033) and the European Union (NextGenerationEU).
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