Spatio-temporal similarity search method for disaster estimation

For fast disaster estimation after a large-scale disaster occurs, this paper presents a fast spatio-temporal similarity search method that searches a database storing many scenarios of disaster simulation results represented by time-series grid data for some scenarios similar to insufficient observed data sent from sensors. The proposed method efficiently processes spatio-temporal intersection by using a spatiotemporal index to reduce the processing time for the spatiotemporal similarity search. Additionally, this paper presents the efficient spatio-temporal range search method by using this spatio-temporal index. The spatio-temporal range search is needed for the analysis and visualization in order to grasp a damage situation after spatio-temporal similarity search returns some scenarios similar to observed data. The results of the performance evaluation show that the proposed method has a shorter response time for the spatiotemporal similarity search than two conventional methods that use a temporal index and a spatial index. They also show that the response time is within about 30 seconds when the proposed method searches the database storing 50 billion time-series grid data items for some scenarios similar to 100 observed data items. As a result, the proposed method can be applied to a real environment in which a spatio-temporal similarity search needs to processed within 10 minutes. Additionally, the evaluation results show that the spatio-temporal range search method by using the spatio-temporal index can be also applied to a real environment.