基于InSAR技术的川西高山峡谷区地质灾害早期识别研究——以小金川河流域为例

doi:10.19388/j.zgdzdc.2022.02.12

Abstract
Figure/Table
References
Related Citation (12)

Download: PDF (7906 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Short Baseline Set Time-Series Interferometry (Small Baseline Subset InSAR,SBAS-InSAR) technology is used to carry out research on surface multi-temporal and long time-series deformation monitoring and early identification of potential geological hazards in the high mountain and valley areas of western Sichuan, combining with the multi-temporal synthetic aperture radar data. The principle of the time-series InSAR method is introduced and the data processing process is sorted out. Besides, the radar visibility of Xiaojinchuan River Basin is analyzed, and the surface deformation monitoring in the basin is carried out using 26 periods of Sentinel-1A historical archived data from November 2018 to December 2019. The results show that the accumulated deformation in the radar line of sight direction in the basin reaches -51.12—75.28 mm/a. 4 deformation anomalies and 11 potential geological hazards were identified based on the distribution pattern of deformation anomalies, including 6 known geological hazards and 5 unknown geological hazards. Taking P1 (Aniangzhai landslide) as an example, the authors in this paper have carried out the long time series monitoring analysis and verification. The reliability of using InSAR technology for early identification of geological hazards were identified to prove the advantages and effectiveness of SBAS-InSAR technology in early identification of geological hazards, which has the potential for wide-scale application in the high mountain and valley areas of western Sichuan.

Key words： SBAS-InSAR high mountain and valley area geological hazard Xiaojinchuan River early identification

Received: 26 February 2021

ZTFLH:

P694

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	TANG Yao
	WANG Lijuan
	LIAO Jun
	DENG Cong

Cite this article:

TANG Yao,WANG Lijuan,LIAO Jun, et al. Research on early identification of geological hazards in high mountain and valley areas of western Sichuan Province based on InSAR technology: A case study of Xiaojinchuan River Basin[J]. , 2022, 9(2): 119-128.

URL:

http://journal25.magtechjournal.com/Jwk_dzdc/EN/10.19388/j.zgdzdc.2022.02.12 OR http://journal25.magtechjournal.com/Jwk_dzdc/EN/Y2022/V9/I2/119

[1] 张路,廖明生,董杰,等.基于时间序列InSAR分析的西部山区滑坡灾害隐患早期识别——以四川丹巴为例[J].武汉大学学报:信息科学版,2018,43(12):2039-2049.
Zhang L,Liao M S,Dong J,et al.Early detection of landslide hazards in mountainous areas of west China using time series SAR interferometry:A case study of Danba,Sichuan[J].Geomat Inform Sci Wuhan Univ,2018,43(12):2039-2049.
[2] 唐尧,王立娟,马国超,等.基于“高分+”的金沙江滑坡灾情监测与应用前景分析[J].武汉大学学报:信息科学版,2019,44(7):1082-1092.
Tang Y,Wang L J,Ma G C,et al.Disaster monitoring and application prospect analysis of the Jinsha river landslide based on “Gaofen+”[J].Geomat Inform Sci Wuhan Univ,2019,44(7):1082-1092.
[3] 王立伟.基于D-InSAR数据分析的高山峡谷区域滑坡位移识别[D].北京:北京科技大学,2015.
Wang L W.Identification of Landslide Displacement in Alpine Valley Region Based on D-InSAR Data Analysis[D].Beijing:University of Science and Technology Beijing,2015.
[4] 王志一,徐素宁,王娜,等.高分辨率光学和SAR遥感影像在地震地质灾害调查中的应用——以九寨沟M7.0级地震为例[J].中国地质灾害与防治学报,2018,29(5):81-88.
Wang Z Y,Xu S N,Wang N,et al.Application of the high resolution optical and SAR remote sensing data images induced by the Jiuzhaigou M7.0 earthquake geological hazards survey[J].Chin J Geol Hazard Control,2018,29(5):81-88.
[5] 许强,董秀军,李为乐.基于天-空-地一体化的重大地质灾害隐患早期识别与监测预警[J].武汉大学学报:信息科学版,2019,44(7):957-966.
Xu Q,Dong X J,Li W L.Integrated space-air-ground early detection,monitoring and warning system for potential catastrophic geohazards[J].Geomat Inform Sci Wuhan Univ,2019,44(7):957-966.
[6] 郭瑞,李素敏,陈娅男,等.基于SBAS-InSAR的矿区采空区潜在滑坡综合识别方法[J].地球信息科学学报,2019,21(7):1109-1120.
Guo R,Li S M,Chen Y N,et al.A method based on SBAS-InSAR for comprehensive identification of potential goaf landslide[J].J Geo-Inform Sci,2019,21(7):1109-1120.
[7] 麻源源,左小清,麻卫峰,等.基于SBAS-InSAR技术对昆明机场高边坡沉降监测研究[J].工程勘察,2018,46(7):22-27,39.
Ma Y Y,Zuo X Q,Ma W F,et al.Kunming airport high slope settlement monitoring based on SBAS-InSAR[J].Geotech Invest Survey,2018,46(7):22-27,39.
[8] 潘超,江利明,孙奇石,等.基于Sentinel-1雷达影像的成都市地面沉降InSAR监测分析[J].大地测量与地球动力学,2020,40(2):198-203.
Pan C,Jiang L M,Sun Q S,et al.Monitoring and analyzing Chengdu ground subsidence based on InSAR technology by using Sentinel-1 radar image[J].J Geod Geodynam,2020,40(2):198-203.
[9] 孙晓鹏,鲁小丫,文学虎,等.基于SBAS-InSAR的成都平原地面沉降监测[J].国土资源遥感,2016,28(3):123-129.
Sun X P,Lu X Y,Wen X H,et al.Monitoring of ground subsi-dence in Chengdu Plain using SBAS-InSAR[J].Remote Sens Land Resour,2016,28(3):123-129.
[10] Herrera G,Gutiérrez F,García-Davalillo J C,et al.Multi-sensor advanced DInSAR monitoring of very slow landslides:The Tena Valley case study (Central Spanish Pyrenees)[J].Remote Sens Environ,2013,128:31-43.
[11] 聂兵其.基于InSAR的滑坡形变探测及隐患识别研究——以丹巴县城区为例[D].成都:成都理工大学,2018.
Nie B Q.Landslide Deformation Detection and Identification Based on InSAR Technology:A Case of Danba County[D].Chengdu:Chengdu University of Technology,2018.