Résumé
As of today, SAR imagery represents the most commonly used data source for remote sensing-based flood mapping. The data are characterized by a good sensitivity to water and are available day and night, regardless of cloud cover. Many studies have demonstrated that SAR systems are suitable tools for flood mapping on bare soils and scarcely vegetated areas. In spite of the progress in the development of Near Real Time SAR based flood mapping algorithms, the detection of inundation in urban areas still represents a critical issue. Here we propose a methodology for identifying floods that heavily affected the city of Houston (Texas) during the 2017 hurricane season. Our approach takes advantage of the Interferometric SAR coherence feature to detect the presence of floodwater in urbanized areas. In particular, data provided by the Sentinel-1 mission in both, Strip Map and Interferometric Wide Swath modes, have been used, with a geometric resolution of 5m and 20m, respectively. The algorithm takes fully advantage of the Sentinel-1 mission's repeat cycle of six days, thereby providing an unprecedented possibility to develop an automatic, high frequency flood mapping application that is suitable for complex environments. The test of the algorithm for the Houston case study showed promising results for mapping flood in urban areas