Composition of simulation data for large-scale disaster estimation
Hideki Hayashi, Akinori Asahara, Natsuko Sugaya, Yuichi Ogawa, Hitoshi Tomita · 2016
When a large-scale natural disaster occurs, it is necessary to quickly collect damage information so that disaster-relief operations and wide-area support in accordance with the scale of the natural disaster can be initiated. Previously, we proposed a fast spatio-temporal similarity search method (called the STSim method) that searches a database storing many scenarios of disaster simulation data represented by time-series grid data for scenarios similar to insufficient observed data sent from sensors. When the STSim method is naively applied for estimating disasters occurring at multiple locations, e.g., fire spreading after a large-scale earthquake, it must prepare a huge number of combinations consisting of scenarios that represent disasters at multiple locations.