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Time Series Analysis on the Damage Report of the Northern Kyushu Heavy Rainfall in July 2017
Author(s) -
Qinglin Cui,
Makoto Hanashima,
Yuichiro Usuda
Publication year - 2020
Publication title -
journal of disaster research
Language(s) - English
Resource type - Journals
eISSN - 1883-8030
pISSN - 1881-2473
DOI - 10.20965/jdr.2020.p0698
Subject(s) - natural disaster , time series , environmental science , meteorology , geography , computer science , machine learning
After a natural disaster occurs, the production and sharing of damage reports are extremely important for a disaster response site. However, one of the problems is that the data shared by the damage reports cannot clearly indicate when the damage situation could be grasped because such data change day by day. Accordingly, in this study, the data of the damage reports of the Headquarters for Disaster Control are treated as unequally spaced time series data to evaluate the changing conditions of the data quantitatively. For this purpose, a case is examined for the Headquarters for Disaster Control of Fukuoka Prefecture at the time of the Northern Kyushu Heavy Rainfall event in July 2017. As a result of the examination, it is indicated that the quantitative evaluation would be possible for 1) analysis on timing when the data of the damage reports are updated, 2) analysis on the characteristics of time series of the report data, and 3) visualization of the progress of the damage report service.

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