Examination of Effectiveness of Flood Area Estimation During Flooding Disasters Using SNS Posts – Case study on Typhoon Hagibis in 2019 –

Jazyk: japonština
Rok vydání: 2022
Předmět:
Zdroj: 防災科学技術研究所 研究報告 = Report of the National Research Institute for Earth Science and Disaster Resilience. 86:1-10
ISSN: 1347-7471
Popis: 令和元年東日本台風は,東日本を中心に記録的な大雨となり,広範囲で河川氾濫や内水氾濫が相次ぎ,浸水被害をもたらした.豪雨期間中にソーシャルネットワーキングサービス(SNS)上にも時々刻々と変化する浸水・冠水等の情報が投稿された.即時性の高いSNS投稿を情報収集ツールに活用できれば,効果的な水災対応につながることができると考えられる.そこで,我々は令和元年東日本台風期間中のSNS投稿を対象とし,ArcGISを用いて参考地点の標高と投稿画像や映像から浸水深に基づく浸水域を推定し,自治体等が公表した浸水実績図等との比較検証を行った.その結果,浸水深0.5 m以上の浸水については状況把握に有効な精度で浸水域を推定することが可能であることが確認できた.Typhoon Hagibis (2019) brought record-breaking heavy rainfall mainly in eastern Japan, causing flooding of rivers and inundation over wide areas. Near real-time information on inundation and flooding, was posted on Social Networking Services (SNS) during and after the heavy rainfall. Such the SNS posts can provide useful information for effective disaster responses. Therefore, we collected SNS posts during Typhoon Hagibis’ rainfall and investigated the possibility of and limitations to estimate inundation areas from SNS using ArcGIS. The floodplain boundaries and inundation depth were estimated based on 5 m resolution digital elevation model published by the Geospatial Information Authority of Japan and the inundation conditions identified from the posted images or videos. Then we compared estimated inundation areas and depths with the inundation record charts provided by the local governments. Our results demonstrated that the inundation area can be estimated with sufficient accuracy for inundation depths of 0.5 m or greater based on SNS posts.
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Databáze: OpenAIRE