Aggregation of heterogeneous data sources for the early acquisition of satellite images in case of flood events

Abstract

Satellite-based emergency mapping is crucial for supporting local disaster response in anticipation of, during and following a disaster. With the increasing frequency of natural disasters like floods and the large availability of web-based and remotely sensed data, there is an opportunity to automate and optimize rapid mapping processes. Early tasking of satellites has already enhanced the timeliness of crisis information products. In this context, ongoing research focuses on automatically deriving potentially affected Areas Of Interest (AOI) by monitoring and aggregating heterogeneous data sources such as official alerts, and remote sensing-based data using a Discrete Global Grid System (DGGS). These AOIs can initiate the early tasking of very-high resolution satellites.