Improving Situational Awareness for Floods: Monitoring Using Satellite Data in the Boreal Region

Abstract

Space-borne remote sensing techniques enable a near real-time mapping of floods cost-efficiently. Synthetic Aperture Radar (SAR) and optical sensors are the most suitable for flood detection, however, SAR has become more popular, due to the independence of sunlight and weather conditions, and the increasing data availability. Typical spring floods occurred in northern Finland during 2018. Various remote sensing sources were utilized for monitoring and damage estimation of the flooding. Floods were mapped with the SAR based Finnish Flood Centre’s Flood Detection Algorithm (FC-FloDA), a standard threshold-based approach applied to Sentinel-1, and a visual interpretation of Sentinel-2 images. In addition, flood maps from the Copernicus Emergency Management Service (EMS) and aerial photographs from the city of Tornio were ordered. The flood products and interpretations were compared, and a deeper accuracy assessment was conducted for the FC-FloDA maps. FC-FloDA was, in general, the most successful in detecting floods within the test areas. The EMS product and the Sentinel-1 interpretation worked well in open areas, but they did not detect floods in forests. The superiority of Flood Centre’s product is mainly based on the adaptation of the algorithm to northern boreal environments and the selection of HH-polarized SAR data instead of VV-pol.