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Early Estimation of Heavy Rain Damage at the Municipal Level Based on Time-Series Analysis of SNS Information
https://nied-repo.bosai.go.jp/records/6583
https://nied-repo.bosai.go.jp/records/658373925693-80ba-452e-b52b-cec03a346666
| Item type | researchmap(1) | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2025-03-24 | |||||||||||||
| タイトル | ||||||||||||||
| 言語 | en | |||||||||||||
| タイトル | Early Estimation of Heavy Rain Damage at the Municipal Level Based on Time-Series Analysis of SNS Information | |||||||||||||
| 言語 | ||||||||||||||
| 言語 | eng | |||||||||||||
| 著者 |
Cui Qinglin
× Cui Qinglin
× Shoyama Kikuko
× Hanashima Makoto
× Usuda Yuichiro
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| 抄録 | ||||||||||||||
| 内容記述タイプ | Other | |||||||||||||
| 内容記述 | To carry out natural disaster response, restoration, and reconstruction, it is important to efficiently and quickly assess the damage caused by the natural disaster. The existing evidence demonstrates that when a natural disaster occurs, social networking services (SNS) information is amplified significantly, compared to normal times. Specifically, the damage caused by a natural disaster tends to cover a wide area and have a large scale. Additionally, it may vary considerably depending on the municipality. Thus, this study investigates whether the utilization of this amplified SNS information can offer an effective approach for real-time evaluation and monitoring of the damage caused by a natural disaster in municipal units. To this end, focusing on time-series changes in SNS information, we propose a general-purpose analysis method of SNS information for evaluating the damage caused by a natural disaster in real time in municipal units. Using real-world data twitter data, we investigate the case of Kumamoto Prefecture, which experienced heavy rain in July 2020 and July 2021, to verify the proposed analysis method. | |||||||||||||
| 言語 | en | |||||||||||||
| 書誌情報 |
en : Journal of Disaster Research 巻 17, 号 6, p. 944-955, 発行日 2022-10-01 |
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| 出版者 | ||||||||||||||
| 言語 | en | |||||||||||||
| 出版者 | Fuji Technology Press Ltd. | |||||||||||||
| ISSN | ||||||||||||||
| 収録物識別子タイプ | EISSN | |||||||||||||
| 収録物識別子 | 1883-8030 | |||||||||||||
| DOI | ||||||||||||||
| 関連識別子 | 10.20965/jdr.2022.p0944 | |||||||||||||
