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Integrating C- and L-Band SAR Imagery for Detailed Flood Monitoring of Remote Vegetated Areas
Article

Improving Urban Flood Mapping by Merging Synthetic Aperture Radar-Derived Flood Footprints with Flood Hazard Maps

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Department of Geography and Environmental Science, University of Reading, Reading RG6 6AB, UK
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JBA Consulting, Broughton Park, Skipton BD23 3FD, UK
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Department of Meteorology, University of Reading, Reading RG6 6ET, UK
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Department of Mathematics and Statistics, University of Reading, Reading RG6 6AX, UK
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Spire Global Ltd., Glasgow G3 8JU, UK
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Department of Earth Sciences, Uppsala University, SE-751 05 Uppsala, Sweden
*
Author to whom correspondence should be addressed.
Academic Editors: Alberto Refice, Domenico Capolongo, Marco Chini and Annarita D’Addabbo
Water 2021, 13(11), 1577; https://doi.org/10.3390/w13111577
Received: 1 May 2021 / Revised: 27 May 2021 / Accepted: 28 May 2021 / Published: 2 June 2021
(This article belongs to the Special Issue Improving Flood Detection and Monitoring through Remote Sensing)
Remotely sensed flood extents obtained in near real-time can be used for emergency flood incident management and as observations for assimilation into flood forecasting models. High-resolution synthetic aperture radar (SAR) sensors have the potential to detect flood extents in urban areas through clouds during both day- and night-time. This paper considers a method for detecting flooding in urban areas by merging near real-time SAR flood extents with model-derived flood hazard maps. This allows a two-way symbiosis, whereby currently available SAR urban flood extent improves future model flood predictions, while flood hazard maps obtained after the SAR overpasses improve the SAR estimate of urban flood extents. The method estimates urban flooding using SAR backscatter only in rural areas adjacent to urban ones. It was compared to an existing method using SAR returns in both rural and urban areas. The method using SAR solely in rural areas gave an average flood detection accuracy of 94% and a false positive rate of 9% in the urban areas and was more accurate than the existing method. View Full-Text
Keywords: image processing; hydrology; synthetic aperture radar image processing; hydrology; synthetic aperture radar
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MDPI and ACS Style

Mason, D.C.; Bevington, J.; Dance, S.L.; Revilla-Romero, B.; Smith, R.; Vetra-Carvalho, S.; Cloke, H.L. Improving Urban Flood Mapping by Merging Synthetic Aperture Radar-Derived Flood Footprints with Flood Hazard Maps. Water 2021, 13, 1577. https://doi.org/10.3390/w13111577

AMA Style

Mason DC, Bevington J, Dance SL, Revilla-Romero B, Smith R, Vetra-Carvalho S, Cloke HL. Improving Urban Flood Mapping by Merging Synthetic Aperture Radar-Derived Flood Footprints with Flood Hazard Maps. Water. 2021; 13(11):1577. https://doi.org/10.3390/w13111577

Chicago/Turabian Style

Mason, David C., John Bevington, Sarah L. Dance, Beatriz Revilla-Romero, Richard Smith, Sanita Vetra-Carvalho, and Hannah L. Cloke 2021. "Improving Urban Flood Mapping by Merging Synthetic Aperture Radar-Derived Flood Footprints with Flood Hazard Maps" Water 13, no. 11: 1577. https://doi.org/10.3390/w13111577

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