It is important to discern in real time the risk level of rain-related disasters such as floods and landslides in order to maintain readiness against heavy-rainfall disasters and to decide on the suitable response measures. In this study, we developed an information processing technology that employs hazard information which indicates the risk of inundation or landslides. It also presents indices of social vulnerability and applies the spatial resolution functions of a geographic information system (GIS) to extract in real time the highly exposed and vulnerable areas that are faced with an increased risk of flooding or landslides. The technology’s validity was verified using a case study – namely, the heavy rainfall that accompanied a pressure front in August, 2019. The results show that, with respect to flood risks, we were able to extract in real time specific areas where flooding may be taking place, thus demonstrating the possibility of applying the technology to decide priorities in disaster response measures. Future issues are related to information dissemination, including the specific labeling and expressions that are easy for the user to understand as well as improving the user interface so as to facilitate delivery of relevant risk information in real time.

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