<scp>Country?wide</scp> flood exposure analysis using Sentinel?1 synthetic aperture radar data: Case study of 2019 Iran flood

Extreme precipitation and flooding often lead to human economic losses. However, the high-resolution nationwide exposure data are scarce. Availability of all-weather space-borne SAR satellite can potentially improve ability generate flood map extent globally. In Iran, is a major concern, given socioeconomic vulnerabilities increased likelihood climate extremes. Iran experienced extreme during January March 2019, attributed significant October 2018 which well above long-term averages for 1999–2019. Using Pettitt Mann Kendall tests, records were identified by decreasing increasing trends in north south, respectively. Utilizing 673 Sentinel-1 intensity images, we applied fast-marching algorithm image segmentation combination with Bayesian framework obtain probabilistic maps. We found, 22, 9, 15 states January, February, March, respectively, that covered >15% their area high flooded percent northwestern southeastern region. estimated >15, >11.32, >11.33 million people exposed floods Our datasets inform models management efforts under extremes changing land use cover.