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Landslides triggered by the 6 September 2018 Mw 6.6 Hokkaido, Japan: an updated inventory and retrospective hazard assessment

山崩由 2018 年 9 月 6 日 Mw 6.6 北海道被触发,日本: 更新的库存和回顾的危险评价

作     者:Cui, Yulong Bao, Pengpeng Xu, Chong Ma, Siyuan Zheng, Jun Fu, Gui 

作者机构:Anhui Univ Sci & Technol Sch Civil Engn & Architecture Huainan 232001 Anhui Peoples R China Minist Emergency Management China Natl Inst Nat Hazards Beijing 100085 Peoples R China China Earthquake Adm Inst Geol Key Lab Act Tecton & Volcano Beijing 100029 Peoples R China Zhejiang Univ Dept Civil Engn Hangzhou 310058 Zhejiang Peoples R China 

出 版 物:《EARTH SCIENCE INFORMATICS》 (地球科学信息学)

年 卷 期:2021年第14卷第1期

页      面:247-258页

核心收录:

学科分类:07[理学] 0708[理学-地球物理学] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

基  金:National Natural Science Foundation of China [41807267, 41661144037] Natural Science Research Project of the Colleges and Universities in Anhui Province [KJ2018A0075] 

主  题:Co-seismic landslides Visual interpretation Landslide inventory Logistic regression model Retrospective hazard assessment 

摘      要:On September 6, 2018, an Mw 6.6 earthquake occurred in Hokkaido, Japan, triggering massive landslides. Based on the 0.3 m-resolution Pleiades-1 satellite image on the Google Earth platform, we constructed an updated co-seismic landslide inventory for this event, which permitted to map 12,586 landslides. These slope failures are featured by a large number, wide spread, large scales, and local dense distribution. Considering nine influence factors, i.e. elevation, slope angle, slope aspect, curvature, distance to road, distance to river, distance to the epicenter, lithology, and topography, the logistic regression model was applied to carry out a retrospective hazard assessment of earthquake-triggered landslides in the affected area, and the rationality of such prediction was verified by the real landslides mapped. Results show that the landslide hazard evaluation map is in good agreement with the actual landslide distribution. The success rate of the hazard assessment map is 87.0% compared to training samples, and 86.5% compared to testing samples, respectively. The updated landslide inventory is a useful complement to the existing landslide inventory maps and the landslide hazard assessment map is helpful for landslide disaster prevention and reduction and reconstruction planning in the affected area.

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