[4N1-GS-3] Knowledge utilization and sharing: social applications

[4N1-GS-3-02] Analysis of Cash Withdrawal Trends in the Case of Localized Heavy Rain by Data Fusion using Location Information

〇Hitomi Sano¹, Naoto Minakawa¹, Hiroki Sakaji¹, Kiyoshi Izumi¹ (1. The University of Tokyo)

Keywords:climate change, financial information, data fusion, water disaster, heavy rain

In recent years, localized heavy rain has occurred frequently, and economic damage cases caused by water disasters are increasing. However, there is no practical method for assessing the impact of the economy and financial system on climate change. This study focuses on localized heavy rain and develops the methods by data fusion using location information of weather information (rainfall observation information) and financial information (statistical information on withdrawals from ATMs). This paper introduces the analysis results of ATM cash withdrawal trends during localized heavy rains.