A new approach for rapid urban flood mapping using ALOS-2/PALSAR-2 in 2015 Kinu River Flood, Japan

A near-real-time algorithm to process satellite synthetic aperture radar (SAR) imagery for urban flood detection still remains a challenge. In this paper, we developed a new floodwater detection algorithm based on SAR backscattered intensity using pre- and post-flood data observed by the Japan Aerospace Exploration Agency's Advanced Land Observing Satellite-2, which provided very high-spatial-resolution L-band SAR images (PALSAR-2 SM1, 2.5 m spatial resolution) in the case of the Kinu River flood. With this algorithm, we first classified land use types in order to analyze the characterization of urban land surface backscatters. Change detection was then conducted for the pilot area using correlation coefficients based on differences in the magnitude of the backscattering intensity derived from building orientation before and right after the flood. In particular, the flooded building was more distinguishable than with a traditional detection method.