Improving urban flood mapping by merging Synthetic Aperture Radar-derived flood footprints with flood hazard maps

Mason, D. ORCID: https://orcid.org/0000-0001-6092-6081, Bevington, J., Dance, S. ORCID: https://orcid.org/0000-0003-1690-3338, Revilla-Romero, B., Smith, R., Vetra-Carvalho, S. and Cloke, H. ORCID: https://orcid.org/0000-0002-1472-868X (2021) Improving urban flood mapping by merging Synthetic Aperture Radar-derived flood footprints with flood hazard maps. Water, 13 (11). 1577. ISSN 2073-4441 doi: 10.3390/w13111577

Abstract/Summary

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 cloud 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 overpass improve the SAR estimate of the urban flood extent. The method estimates urban flooding using SAR backscatter only in rural areas adjacent to the urban ones. It was compared to an existing method using SAR returns in both the 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.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/98486
Item Type	Article
Refereed	Yes
Divisions	Science > School of Archaeology, Geography and Environmental Science > Department of Geography and Environmental Science Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	MDPI
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