A Multi-Sensor System for Surface Water Extraction: Application Examples in the Context of Disaster Management

Remote sensing data has become an essential part of today’s disaster management activities. In recent years, the German Aerospace Center (DLR) has developed a multi-sensor system for automatic and large-scale surface water extraction to support disaster management activities in the context of hydrological extreme events on a global level. The system consists of several cloud-based, automated processing chains that uses convolutional neural networks (CNN) to extract the surface water extent from radar and multi-spectral satellite data (e.g. Sentinel-1/2, Landsat, TerraSAR-X, very high-resolution (VHR) optical satellite missions). Within this contribution, four application examples of the proposed system in the frame of floods and hydrologic drought events are given.