Articles | Volume 24, issue 8
https://doi.org/10.5194/nhess-24-2817-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-24-2817-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Aug 2024
Research article |
| 22 Aug 2024
| 22 Aug 2024
Water depth estimate and flood extent enhancement for satellite-based inundation maps
Andrea Betterle
CORRESPONDING AUTHOR
European Commission, Joint Research Centre, Ispra, Italy
Peter Salamon
European Commission, Joint Research Centre, Ispra, Italy
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Cited
21 citations as recorded by crossref.
- Geospatial and Deep Learning Approaches for Modeling Floodwater Depth in Urbanized Areas J. Blay & L. Hashemi-Beni https://doi.org/10.3390/rs18010060
- Flood hazard assessment due to dam breaching considering river morphodynamics A. Graziano et al. https://doi.org/10.1007/s11069-025-07658-6
- A Simplified Multi-Hazard Framework for the Protection of Coastal Salt Pond Systems D. Rapti & S. Valkaniotis https://doi.org/10.3390/environments13070400
- Association between flood exposure and chronic kidney disease: A nationwide cross-sectional study in China Y. Qin et al. https://doi.org/10.1016/j.envres.2025.123631
- A hybrid technique for flood inundation detection using Pareto scaling normalization and bayesian probability P. Hazra et al. https://doi.org/10.2166/wpt.2026.279
- Under cloud and canopy: enhancing the dynamic surface water eXtent − harmonized landsat sentinel-2 (DSWx-HLS) flood maps with terrain-based flood propagation S. Do et al. https://doi.org/10.1016/j.isprsjprs.2026.10.045
- Advancing Flood Detection and Mapping: A Review of Earth Observation Services, 3D Data Integration, and AI-Based Techniques T. Destefanis et al. https://doi.org/10.3390/rs17172943
- Modelling the impact of physical climate risk and adaptation on sovereign credit ratings M. Bernhofen et al. https://doi.org/10.1093/oxrep/grag026
- Flood depth mapping with SWOT-derived training data: evaluating the potential of open-source datasets Z. Li et al. https://doi.org/10.1016/j.jhydrol.2026.136000
- Calibration framework for complex 2D hydrodynamic models: Use of satellite-derived flood extent and water depth data, and evaluation with various performance metrics I. Zotou et al. https://doi.org/10.1016/j.advwatres.2025.105066
- Enhancing inundation mapping with geomorphological segmentation: Filling in gaps in spectral observations M. Rossi & R. Vervoort https://doi.org/10.1016/j.scitotenv.2025.180180
- FlDepth: A New Method for Estimating Fluvial and Pluvial Flood Depths from Near Real-Time Satellite-Derived Inundation Map and Topography A. Akkimi et al. https://doi.org/10.1007/s11269-025-04405-1
- Enhanced large-scale flood mapping using data-efficient unsupervised framework based on morphological active contour model and single synthetic aperture radar image R. Soudagar et al. https://doi.org/10.1016/j.jenvman.2025.124836
- Evaluating the effects of preprocessing, method selection, and hyperparameter tuning on SAR-based flood mapping and water depth estimation J. Travert et al. https://doi.org/10.5194/nhess-26-2387-2026
- Data assimilation of flood maps in a 2D flood model for different performance measures J. Travert et al. https://doi.org/10.1007/s10596-026-10452-3
- Bottom-up estimates of population exposure and damage from floods: A case study on Malawi's 2015 floods S. Ngorok et al. https://doi.org/10.1016/j.ijdrr.2026.106552
- Automated urban flood level detection based on flooded bus dataset using YOLOv8 Y. Qiu et al. https://doi.org/10.5194/nhess-25-3525-2025
- Flood and Rice Damage Mapping for Tropical Storm Talas in Vietnam Using Sentinel-1 SAR Data P. van Rutten et al. https://doi.org/10.3390/rs17132171
- Predicting multi period flood cascades and community failure in EV charging networks Y. Wan et al. https://doi.org/10.1038/s44304-025-00164-6
- Glacial lake outburst flood hazard and downstream impacts: lessons from Afghanistan examples F. Azizi et al. https://doi.org/10.1007/s11069-026-08449-3
- FLDSensing: Remote Sensing Flood Inundation Mapping with FLDPLN J. Edwards et al. https://doi.org/10.3390/rs17193362
21 citations as recorded by crossref.
- Geospatial and Deep Learning Approaches for Modeling Floodwater Depth in Urbanized Areas J. Blay & L. Hashemi-Beni https://doi.org/10.3390/rs18010060
- Flood hazard assessment due to dam breaching considering river morphodynamics A. Graziano et al. https://doi.org/10.1007/s11069-025-07658-6
- A Simplified Multi-Hazard Framework for the Protection of Coastal Salt Pond Systems D. Rapti & S. Valkaniotis https://doi.org/10.3390/environments13070400
- Association between flood exposure and chronic kidney disease: A nationwide cross-sectional study in China Y. Qin et al. https://doi.org/10.1016/j.envres.2025.123631
- A hybrid technique for flood inundation detection using Pareto scaling normalization and bayesian probability P. Hazra et al. https://doi.org/10.2166/wpt.2026.279
- Under cloud and canopy: enhancing the dynamic surface water eXtent − harmonized landsat sentinel-2 (DSWx-HLS) flood maps with terrain-based flood propagation S. Do et al. https://doi.org/10.1016/j.isprsjprs.2026.10.045
- Advancing Flood Detection and Mapping: A Review of Earth Observation Services, 3D Data Integration, and AI-Based Techniques T. Destefanis et al. https://doi.org/10.3390/rs17172943
- Modelling the impact of physical climate risk and adaptation on sovereign credit ratings M. Bernhofen et al. https://doi.org/10.1093/oxrep/grag026
- Flood depth mapping with SWOT-derived training data: evaluating the potential of open-source datasets Z. Li et al. https://doi.org/10.1016/j.jhydrol.2026.136000
- Calibration framework for complex 2D hydrodynamic models: Use of satellite-derived flood extent and water depth data, and evaluation with various performance metrics I. Zotou et al. https://doi.org/10.1016/j.advwatres.2025.105066
- Enhancing inundation mapping with geomorphological segmentation: Filling in gaps in spectral observations M. Rossi & R. Vervoort https://doi.org/10.1016/j.scitotenv.2025.180180
- FlDepth: A New Method for Estimating Fluvial and Pluvial Flood Depths from Near Real-Time Satellite-Derived Inundation Map and Topography A. Akkimi et al. https://doi.org/10.1007/s11269-025-04405-1
- Enhanced large-scale flood mapping using data-efficient unsupervised framework based on morphological active contour model and single synthetic aperture radar image R. Soudagar et al. https://doi.org/10.1016/j.jenvman.2025.124836
- Evaluating the effects of preprocessing, method selection, and hyperparameter tuning on SAR-based flood mapping and water depth estimation J. Travert et al. https://doi.org/10.5194/nhess-26-2387-2026
- Data assimilation of flood maps in a 2D flood model for different performance measures J. Travert et al. https://doi.org/10.1007/s10596-026-10452-3
- Bottom-up estimates of population exposure and damage from floods: A case study on Malawi's 2015 floods S. Ngorok et al. https://doi.org/10.1016/j.ijdrr.2026.106552
- Automated urban flood level detection based on flooded bus dataset using YOLOv8 Y. Qiu et al. https://doi.org/10.5194/nhess-25-3525-2025
- Flood and Rice Damage Mapping for Tropical Storm Talas in Vietnam Using Sentinel-1 SAR Data P. van Rutten et al. https://doi.org/10.3390/rs17132171
- Predicting multi period flood cascades and community failure in EV charging networks Y. Wan et al. https://doi.org/10.1038/s44304-025-00164-6
- Glacial lake outburst flood hazard and downstream impacts: lessons from Afghanistan examples F. Azizi et al. https://doi.org/10.1007/s11069-026-08449-3
- FLDSensing: Remote Sensing Flood Inundation Mapping with FLDPLN J. Edwards et al. https://doi.org/10.3390/rs17193362
Saved (final revised paper)
Latest update: 12 Nov 2026
Short summary
The study proposes a new framework, named FLEXTH, to estimate flood water depth and improve satellite-based flood monitoring using topographical data. FLEXTH is readily available as a computer code, offering a practical and scalable solution for estimating flood depth quickly and systematically over large areas. The methodology can reduce the impacts of floods and enhance emergency response efforts, particularly where resources are limited.
The study proposes a new framework, named FLEXTH, to estimate flood water depth and improve...
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