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Early identification of landslide hazards in deep cut alpine canyon using SBAS-InSAR technology

Authors :
Dingyi ZHOU
Xiaoqing ZUO
Wenfei XI
Bo XIAO
Rui BI
Xin FAN
Source :
Zhongguo dizhi zaihai yu fangzhi xuebao, Vol 33, Iss 2, Pp 16-24 (2022)
Publication Year :
2022
Publisher :
Editorial Office of The Chinese Journal of Geological Hazard and Control, 2022.

Abstract

In recent years, landslides occurred frequently in mountain and gorge areas, which brought serious threats to people's life and property safety. Most scholars use SAR single-track data for early identification of landslides in alpine and canyon areas, but some landslides cannot be identified due to geometric distortion of SAR imaging, and the identification results are not comprehensive. In order to carry out comprehensive and accurate early identification of landslide hazards in alpine valley area, this paper adopts bas-INSAR technology, takes the deep cut alpine valley area along the Xiaojiang River in Dongchuan as the research area, and adopts the combination of SAR data of lifting and lowering orbit to identify landslide hazards, and introduces high-resolution optical images as auxiliary identification. Finally, 18 landslide disaster bodies were identified, among which 5 were high-risk potential landslides, and three types of typical potential landslides were analyzed. The analysis results show that the use of elevator rail SAR data combined with complementary way, can effectively avoid the SAR single orbital data geometric distortion problem in mountain valley area, at the same time, this method can more accurately comprehensively to early identification of alpine valley area of landslide hazard, the cause of disaster prevention and mitigation and government decision-making provides a effective means.

Details

Language :
Chinese
ISSN :
10038035
Volume :
33
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Zhongguo dizhi zaihai yu fangzhi xuebao
Publication Type :
Academic Journal
Accession number :
edsdoj.116b791dad874c55bd0192970381e7ba
Document Type :
article
Full Text :
https://doi.org/10.16031/j.cnki.issn.1003-8035.2022.02-03