Satellite imaging is a critical technology for monitoring and responding to natural disasters such as flooding. Despite the capabilities of modern satellites, there is still much to be desired from the perspective of first response organisations like UNICEF. Two main challenges are rapid access to data, and the ability to automatically identify flooded regions in images. We describe a prototypical flood segmentation system, identifying cloud, water and land, that could be deployed on a constellation of small satellites, performing processing on board to reduce downlink bandwidth by 2 orders of magnitude. We target PhiSat-1, part of the FSSCAT mission, which is planned to be launched by the European Space Agency (ESA) near the start of 2020 as a proof of concept for this new technology.
Joshua Veitch-Michaelis, Gonzalo Mateo-Garcia, Silviu Oprea, Lewis Smith, Atılım Güneş Baydin, Dietmar Backes, Yarin Gal, Guy Schumann
Spotlight talk, Artificial Intelligence for Humanitarian Assistance and Disaster Response (AI+HADR) NeurIPS 2019 Workshop