Detection of Active Landslides in Southwest China using Sentinel-1 and ALOS-2 Data

被引:7
|
作者
Zhang, Teng [1 ]
Xie, Shuai [2 ]
Fan, Jinghui [3 ]
Huang, Bo [4 ]
Wang, Qun [5 ]
Yuan, Weilin [3 ]
Zhao, Hongli [3 ]
Chen, JianPing [1 ]
Li, Hongzhou [6 ]
Liu, Guang [7 ]
Tong, Liqiang [3 ]
Sousa, Joaquim J. [8 ,9 ]
机构
[1] China Univ Geosci, Sch Earth Sci & Resources, Beijing, Peoples R China
[2] Beijing Municipal Commiss Transport, Beijing, Peoples R China
[3] China Aero Geophys Survey & Remote Sensing Ctr Na, Beijing, Peoples R China
[4] Hebei Hydrol Engn Geol Explorat Inst, Shijiazhuang, Hebei, Peoples R China
[5] China Highway Engn Consultants Corp, Beijing, Peoples R China
[6] MNR, Land Satellite Remote Sensing Applicat Ctr, Beijing, Peoples R China
[7] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing, Peoples R China
[8] Univ Tras Os Montes & Alto Douro, Vila Real, Portugal
[9] INESC TEC, Porto, Portugal
基金
中国国家自然科学基金;
关键词
Landslide; Southwest China; D-InSAR; Stacking; ALOS-2; Sentinel-1;
D O I
10.1016/j.procs.2021.01.311
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Synthetic aperture radar interferometry (InSAR) is the technique capable of monitoring active landslide in all-weather conditions and in a near real-time. In this study, ALOS-2 (L-band) and Sentinel-1 (C-Band) images were used to map potential areas prone to the occurrence of large-scale landslide disasters. Differential InSAR (D-InSAR) and multi-temporal techniques were applied to detect landslides in a part of Maoxian(a typical mountainous county in Southwest China), allowing the identification of 8 active landslides. The integration of local historical geological hazard data and local field exploration data allowed to conclude that the detected landslides found in Baibu village and other places were in the development stage. Deformation rate reached 200mm/yr along the line of sight direction. The results obtained by exploiting the two datasets correspond to each other in terms of spatial distribution and are consistent with the local field exploration results. L-band ALOS-2 SAR data proved to be very effective for detecting short-term and severe ground deformation, which is suitable for monitoring deformation in mountainous areas with a certain degree of vegetation coverage. (C) 2021 The Authors. Published by Elsevier B.V.
引用
收藏
页码:1138 / 1145
页数:8
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