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 ΦSat-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.
|Number of pages||6|
|Publication status||Published - 13 Dec 2019|
|Event||Artificial Intelligence for Humanitarian Assistance and Disaster Response Workshop @ NeurIPS 2019 - Vancouver, Canada|
Duration: 13 Dec 2019 → 13 Dec 2019
|Conference||Artificial Intelligence for Humanitarian Assistance and Disaster Response Workshop @ NeurIPS 2019|
|Abbreviated title||AI + HADR 2019|
|Period||13/12/19 → 13/12/19|