The Use of Sentinel-1 Time-Series Data to Improve Flood Monitoring in Arid Areas

• Main Authors: Sandro Martinis, Simon Plank, Kamila Ćwik
• Format: Article
• Language: English
• Published: MDPI AG 2018-04-01
• Series: Remote Sensing
• Subjects: SAR (Synthetic Aperture Radar); water bodies; inundation; flood detection; Sentinel-1; time-series; sand surfaces; arid areas
• Online Access: http://www.mdpi.com/2072-4292/10/4/583

Due to the similarity of the radar backscatter over open water and over sand surfaces a reliable near real-time flood mapping based on satellite radar sensors is usually not possible in arid areas. Within this study, an approach is presented to enhance the results of an automatic Sentinel-1 flood processing chain by removing overestimations of the water extent related to low-backscattering sand surfaces using a Sand Exclusion Layer (SEL) derived from time-series statistics of Sentinel-1 data sets. The methodology was tested and validated on a flood event in May 2016 at Webi Shabelle River, Somalia and Ethiopia, which has been covered by a time-series of 202 Sentinel-1 scenes within the period June 2014 to May 2017. The approach proved capable of significantly improving the classification accuracy of the Sentinel-1 flood service within this study site. The Overall Accuracy increased by ~5% to a value of 98.5% and the User’s Accuracy increased by 25.2% to a value of 96.0%. Experimental results have shown that the classification accuracy is influenced by several parameters such as the lengths of the time-series used for generating the SEL.