This analysis demonstrates improved estimation accuracy for isolated settlements in disaster scenarios, highlighting the importance of multi-sensing data and real-time information.
In the event of a disaster, the occurrence of isolated settlements necessitates prompt responses, including rescue operations, medical transport, and the delivery of essential supplies. However, it is often challenging to quickly identify which areas are isolated. This study developed a method for estimating isolated settlements during earthquake disasters using multi-sensing data. An accuracy evaluation based on data from the 2024 Noto Peninsula earthquake revealed an overlook rate of approximately 60% and a mistaken estimation rate of approximately 20%. By incorporating actual road traffic data, the estimation was refined to extract settlements at high risk of isolation. Moreover, the method successfully identified isolated settlements that were not reported in official damage reports, indicating relatively high estimation accuracy. This capability is expected to assist disaster management headquarters in identifying priority areas for emergency response. Because the data used in the proposed method can be obtained during actual disaster events, the estimation process can be initiated promptly across Japan immediately after an earthquake, thereby enabling the timely provision of valuable information for disaster response. This analysis presents the necessary data and computational approaches for improving estimation accuracy and supporting practical implementation in disaster management. In the future, advancements in various sensing technologies and the development of data-sharing frameworks are expected to facilitate even more accurate estimations.
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Fujita et al. (2025) studied this question.
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