Abstract
During Hurricane Irma’s passage over Florida in September 2017, many sections of the state experienced heavy rain and sequent flooding. In order to drain water out of potential flooding zones and assess property damage, it is important to map the extent and magnitude of the flooded areas at various stages of the storm. We use Synthetic Aperture Radar (SAR) and Interferometric SAR (InSAR) observations, acquired by Sentinel-1 before, during and after the hurricane passage, which enable us to evaluate surface condition during different stages of the hurricane. This study uses multi-temporal images acquired under dry condition before the hurricane to constrain the background backscattering signature. Flooded areas are detected when the backscattering during the hurricane is statistically significantly different from the average dry conditions. The detected changes can be either an increase or decrease of the backscattering, which depends on the scattering characteristics of the surface. In addition, water level change information in Palmdale, South Florida is extracted from an interferogram with the aid of a local water gauge as the reference. The results of our flooding analysis revealed that the majority of the study area in South Florida was flooded during Hurricane Irma.