Flood detection in urban areas using TerraSAR-X

Mason, D.C. ORCID: https://orcid.org/0000-0001-6092-6081, Speck, R., Devereux, B., Schumann, G.J.-P., Neal, J.C. and Bates, P.D. (2010) Flood detection in urban areas using TerraSAR-X. IEEE Transactions on Geoscience and Remote Sensing, 48 (2). pp. 882-894. ISSN 0196-2892 doi: 10.1109/TGRS.2009.2029236

Abstract/Summary

Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X Synthetic Aperture Radar (SAR) data to detect flooded regions in urban areas is described. The study uses a TerraSAR-X image of a 1 in 150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SAR End-To-End simulator (SETES) was used in conjunction with airborne scanning laser altimetry (LiDAR) data to estimate regions of the image in which water would not be visible due to shadow or layover caused by buildings and taller vegetation. A semi-automatic algorithm for the detection of floodwater in urban areas is described, together with its validation using the aerial photographs. 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. The algorithm is aimed at producing urban flood extents with which to calibrate and validate urban flood inundation models, and these findings indicate that TerraSAR-X is capable of providing useful data for this purpose.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/1645
Identification Number/DOI	10.1109/TGRS.2009.2029236
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Environmental Systems Science Centre
Uncontrolled Keywords	Algorithms , hydrology , image processing , simulation
Publisher	IEEE Geoscience and Remote Sensing Society
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