6533b859fe1ef96bd12b81b5
RESEARCH PRODUCT
Flood Detection On Low Cost Orbital Hardware
Gonzalo Mateo-garciaSilviu OpreaLewis SmithJosh Veitch-michaelisGuy SchumannYarin GalAt��l��m G��ne�� BaydinDietmar Backessubject
FOS: Computer and information sciences: Computer science [C05] [Engineering computing & technology]Computer Science - Machine LearningImage and Video Processing (eess.IV): Multidisciplinary general & others [C99] [Engineering computing & technology]Machine Learning (stat.ML)Image and Video ProcessingElectrical Engineering and Systems Science - Image and Video Processing: Sciences informatiques [C05] [Ingénierie informatique & technologie]Machine Learning (cs.LG)Machine Learning: Multidisciplinaire généralités & autres [C99] [Ingénierie informatique & technologie]Artificial IntelligenceStatistics - Machine LearningSmall SatellitesFOS: Electrical engineering electronic engineering information engineeringFlood detectionEarth Observation: Aerospace & aeronautics engineering [C01] [Engineering computing & technology]: Ingénierie aérospatiale [C01] [Ingénierie informatique & technologie]description
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-10-01 |