Landslide Hazard Assessment Combined with InSAR Deformation: A Case Study in the Zagunao River Basin, Sichuan Province, Southwestern China

被引:7
|
作者
Shan, Yunfeng [1 ]
Xu, Zhou [1 ]
Zhou, Shengsen [1 ]
Lu, Huiyan [1 ]
Yu, Wenlong [1 ]
Li, Zhigang [1 ]
Cao, Xiong [2 ]
Li, Pengfei [3 ]
Li, Weile [1 ,4 ]
机构
[1] Chengdu Univ Technol, State Key Lab Geohazard Prevent & Geoenvironm Prot, Chengdu 610059, Peoples R China
[2] China Petr Engn Construct Co Ltd, Southwest Branch, Chengdu 610041, Peoples R China
[3] Guiyang Engn Corp Ltd Power China, Guiyang 550081, Peoples R China
[4] Lab Landslide Risk Early Warning & Control, Chengdu 610059, Peoples R China
关键词
landslides; hazard assessment; InSAR; deformation; Zagunao River; LOGISTIC-REGRESSION; SUSCEPTIBILITY ASSESSMENT; MODELS; GIS; INVENTORY; RESERVOIR;
D O I
10.3390/rs16010099
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Landslides are common natural disasters that cause serious damage to ecosystems and human societies. To effectively prevent and mitigate these disasters, an accurate assessment of landslide hazards is necessary. However, most traditional landslide hazard assessment methods rely on static assessment factors while ignoring the dynamic changes in landslides, which may lead to false-positive errors in the assessment results. This paper presents a novel landslide hazard assessment method for the Zagunao River basin, China. In this study, an updated landslide inventory was obtained for the Zagunao River basin using data from interferometric synthetic aperture radar (InSAR) and optical images. Based on this inventory, a landslide susceptibility map was developed using a random forest algorithm. Finally, an evaluation matrix was created by combining the results of deformation rates from both ascending and descending data to establish a hazard level that considers surface deformation. The method presented in this study can reflect recent landslide hazards in the region and produce dynamic assessments of regional landslide hazards. It provides a basis for the government to identify and manage high-risk areas.
引用
收藏
页数:23
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