Study on hotspot detection for large scale spatiotemporal data

April 01, 2016

◆Grant-in-Aid for Scientific Research (JSPS) "Young Scientists (B)"

◆Leader : ISHIOKA Fumio

◆FY2016 - FY2018

The detection of problems such as the generation status of infective diseases or hazard maps of natural disasters is very basic and important. Some powerful and useful tools such as geographical information systems (GISs) are available, but it is very difficult to determine the location of space-time clusters for various types of spatial data in large quantities or with large time series. The aim of this study is to establish methods to identify a high or low contaminant cluster, so-called hotspot, for various kinds of spatiotemporal spatial data and to develop a software for that.