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--- |
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license: cc-by-nc-4.0 |
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--- |
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This repository contains the trained models of the publication: |
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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. |
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We include the trained models: |
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* **sm_unet_s2** Model trained on the Sentinel-2 L1C bands `["B02", "B03", "B04", "B08", "B11", "B12"]` from the S1S2Water and WorldFloods datasets. |
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* **sm_unet_s1** Model trained on the Sentinel-1 GRD data (`[VV, VH]` channels) from the S1S2Water and Kuro Siwo datasets. |
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* **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. |
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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. |
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<!-- <img src="https://raw.githubusercontent.com/IPL-UV/cloudsen12_models/main/notebooks/example_flood_dubai_2024.png"> --> |
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If you find this work useful please cite: |
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``` |
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@article{PORTALESJULIA2025114882, |
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title = {Understanding flood detection models across Sentinel-1 and Sentinel-2 modalities and benchmark datasets}, |
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journal = {Remote Sensing of Environment}, |
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volume = {328}, |
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pages = {114882}, |
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year = {2025}, |
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issn = {0034-4257}, |
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doi = {https://doi.org/10.1016/j.rse.2025.114882}, |
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url = {https://www.sciencedirect.com/science/article/pii/S003442572500286X}, |
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author = {Enrique Portalés-Julià and Gonzalo Mateo-García and Luis Gómez-Chova}, |
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keywords = {Flood detection, Deep learning, Multimodal fusion, Multispectral, SAR, Sentinel-1, Sentinel-2}, |
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} |
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``` |
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## Licence |
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<img src="https://mirrors.creativecommons.org/presskit/buttons/88x31/png/by-nc.png" alt="licence" width="60"/> |
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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) |
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The `udl4fl` python package is published under a [GNU Lesser GPL v3 licence](https://www.gnu.org/licenses/lgpl-3.0.en.html) |
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## Acknowledgments |
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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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> <img src="https://www.uv.es/chovago/logos/logoMICIN.jpg" alt="DEEPCLOUD project (PID2019-109026RB-I00, University of Valencia) funded by MCIN/AEI/10.13039/501100011033." title="DEEPCLOUD project (PID2019-109026RB-I00, University of Valencia) funded by MCIN/AEI/10.13039/501100011033." width="300"/> |
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