Latent landslide hazard recognition in Fang County using synthetic aperture radar interferometry and geological data

被引:0
|
作者
Wang, Shunyao [1 ,2 ,3 ]
Fan, Qingbin [1 ]
Li, Hui [1 ]
机构
[1] Nanyang Normal Univ, Sch Geog & Tourism, Nanyang, Peoples R China
[2] Nanyang Normal Univ, Key Lab Nat Disaster & Remote Sensing Henan Prov, Nanyang, Peoples R China
[3] Nanyang Normal Univ, Engn Res Ctr Environm Laser Remote Sensing Technol, Nanyang, Peoples R China
关键词
landslide; InSAR; geological data; hazard recognition; Fang County; SAR INTERFEROMETRY; CHINA LANDSLIDE; DEFORMATION; SUSCEPTIBILITY; VALIDATION; IMAGERY; MODELS;
D O I
10.3389/feart.2025.1531615
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The northwest part of Hubei Province, China, is characterized by steep topography, complex geological structures, and intense precipitation, providing ideal natural conditions for landslide disasters. To address the lack of integration of synthetic aperture radar interferometry (InSAR) and geological data for the identification of latent landslide hazards, in this study, we incorporated InSAR technology and geological data to identify potential landslides in Fang County, northwest Hubei Province. With the aid of 10 ALOS-2 data scenes and high-precision digital elevation models of the study area, a displacement rate map with a maximum value of -70.6 mm/a was extracted. Then, according to the displacement rate and optical images, the suspected latent landslide area was delineated, and a comprehensive analysis of the slope map and fault and watershed buffer zone map was performed to obtain the final results. Compared to the existing latent landslide recognition method, the proposed method integrating InSAR and geological data can eliminate areas where landslides are geologically unlikely to occur, thereby enhancing the efficiency and accuracy of latent landslide hazard identification. The results were verified using geological and optical image features, which confirmed its effectiveness for identifying latent landslide hazards. The results of this research can contribute to the prediction and early warning of landslides and guide field investigations of geological disasters.
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页数:11
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