Floodwater detection in urban areas using Sentinel-1 and WorldDEM data

Mason, D. C. ORCID: https://orcid.org/0000-0001-6092-6081, Dance, S. L. ORCID: https://orcid.org/0000-0003-1690-3338 and Cloke, H. L. ORCID: https://orcid.org/0000-0002-1472-868X (2021) Floodwater detection in urban areas using Sentinel-1 and WorldDEM data. Journal of Applied Remote Sensing, 15 (3). 032003. ISSN 1931-3195 doi: 10.1117/1.JRS.15.032003

Abstract/Summary

Remote sensing using Synthetic Aperture Radar (SAR) is an important tool for emergency flood incident management. At present operational services are mainly aimed at flood mapping in rural areas, as mapping in urban areas is hampered by the complicated backscattering mechanisms occurring there. A method for detecting flooding at high resolution in urban areas that may contain dense housing is presented. This largely uses remotely sensed data sets that are readily available on a global basis, including open-access Sentinel-1 SAR data, the WorldDEM Digital Surface Model (DSM), and open-access World Settlement Footprint data to identify urban areas. The method is a change detection technique that estimates flood levels in urban areas locally. It searches for increased SAR backscatter in the post-flood image due to double scattering between water (rather than unflooded ground) and adjacent buildings, and reduced SAR backscatter in areas away from high slopes. Areas of urban flooding are detected by comparing an interpolated flood level surface to the DSM. The method was tested on two flood events that occurred in the UK during the storms of Winter 2019-20. High urban flood detection accuracies were achieved for the event in moderate density housing. The accuracy reduced for the event in dense housing, when street widths became comparable to the DSM resolution, though would still be useful for incident management. The method has potential for operational use for detecting urban flooding in near real-time on a global basis.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/95506
Identification Number/DOI	10.1117/1.JRS.15.032003
Refereed	Yes
Divisions	Science > School of Archaeology, Geography and Environmental Science > Earth Systems Science 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	Society of Photo-optical Instrumentation Engineers (SPIE)
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