Abstract/Summary

Detection of flooding in rural areas is now commonly performed by high resolution Synthetic Aperture Radar (SAR) sensors. However, flooding in urban areas causes the greater risk to lives and property. Urban flood detection is more challenging due to SAR shadow, layover and double scattering effects. Nevertheless, it may often be identified using the fact that, in a post-flood image, double scattering between building walls and adjacent floodwater generally exceeds that in a pre-flood image, where double scattering occurs between buildings and adjacent ground. However, in the event of the urban region being deeply flooded, only a part of the building walls may remain above the flood level, so that the post-flood double scattering may reduce and a flooded region may be misclassified as non-flooded. We investigate whether flood detection can be improved for deeper urban floods by using interferometric coherence as an adjunct to double scattering. An urban area that is not flooded should often exhibit high coherence between image pairs, whereas if there is flooding in one of the images the coherence should be low. An urban flood in Japan that contained deep-flooded, shallow-flooded and non-flooded areas was used as a test example. It was imaged by Sentinel-1, and WorldDEM Digital Surface Model data was used to estimate flood depth and building orientation. An analysis of double scatterers of low post-/pre-flood brightness ratio was carried out for deeply flooded and non-flooded urban double scatterers. It was shown that, using coherence, 58% of the deeply flooded buildings could be detected at the cost of a 16% false positive rate. Without the use of coherence to supplement brightness ratio, all these deeply flooded buildings would be misclassified as non-flooded. This finding could be of use in automating the detection of urban flooding as an aid to flood risk management.