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A genetic-type algorithm is presented that uses satellite geospatial data to determine the most probable path to safety for individuals in a disaster area, where a traditional routing system cannot be used. The algorithm uses geological features and disaster information to determine the shortest safe path. It predicts how a flood can change a landform over time and uses this data to predict alternate routes. It also predicts safe routes in rural locations where GPS/map-based routing data is unavailable or inaccurate. Reflectance and a supervised classification algorithm are used and the output is compared with RFPI and PCR-GLOBWB data.
Rahul Gomes andJeremy Straub
"Genetic algorithm for flood detection and evacuation route planning", Proc. SPIE 10198, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII, 1019816 (5 May 2017); https://doi.org/10.1117/12.2266474
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Rahul Gomes, Jeremy Straub, "Genetic algorithm for flood detection and evacuation route planning," Proc. SPIE 10198, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIII, 1019816 (5 May 2017); https://doi.org/10.1117/12.2266474