Deformation, structure and potential hazard of a landslide based on InSAR in Banbar county, Xizang (Tibet)

被引:0
|
作者
Zhao, Guan-hua [1 ,2 ]
Lan, Heng-xing [2 ,3 ,4 ]
Yin, Hui-yong [1 ]
Li, Lang-ping [2 ,5 ]
Strom, Alexander [6 ]
Sun, Wei-feng [3 ]
Tian, Chao-yang [3 ]
机构
[1] Shandong Univ Sci & Technol, Coll Earth Sci & Engn, Qingdao 266590, Peoples R China
[2] Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
[3] Changan Univ, Sch Geol Engn & Geomat, Xian 710054, Peoples R China
[4] Minist Nat Resources, Key Lab Ecol Geol & Disaster Prevent, Xian 710054, Peoples R China
[5] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[6] JSC Hydroproject Inst, Moscow 125993, Russia
基金
中国国家自然科学基金;
关键词
Landslide; InSAR; Human activity; Deformation; Structure; LSTM model; Engineering construction; Thickness; Neural network; Machine learning; Prediction and prevention; Tibetan Plateau; Geological hazards survey engineering; CROSS-SECTION RESTORATION; VOLUME; SUSCEPTIBILITY; TOPOGRAPHY; KINEMATICS; THICKNESS; MOVEMENT; TOPSAR; CITY;
D O I
10.31035/cg2023130
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The Tibetan Plateau is characterized by complex geological conditions and a relatively fragile ecological environment. In recent years, there has been continuous development and increased human activity in the Tibetan Plateau region, leading to a rising risk of landslides. The landslide in Banbar County, Xizang (Tibet), have been perturbed by ongoing disturbances from human engineering activities, making it susceptible to instability and displaying distinct features. In this study, small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) technology is used to obtain the Line of Sight (LOS) deformation velocity field in the study area, and then the slope-orientation deformation field of the landslide is obtained according to the spatial geometric relationship between the satellite's LOS direction and the landslide. Subsequently, the landslide thickness is inverted by applying the mass conservation criterion. The results show that the movement area of the landslide is about 6.57x10(4) m(2), and the landslide volume is about 1.45x10(6) m(3). The maximum estimated thickness and average thickness of the landslide are 39 m and 22 m, respectively. The thickness estimation results align with the findings from on-site investigation, indicating the applicability of this method to large-scale earth slides. The deformation rate of the landslide exhibits a notable correlation with temperature variations, with rainfall playing a supportive role in the deformation process and displaying a certain lag. Human activities exert the most substantial influence on the spatial heterogeneity of landslide deformation, leading to the direct impact of several prominent deformation areas due to human interventions. Simultaneously, utilizing the long short -term memory (LSTM) model to predict landslide displacement, and the forecast results demonstrate the effectiveness of the LSTM model in predicting landslides that are in a continuous development and movement phase. The landslide is still active, and based on the spatial heterogeneity of landslide deformation, new recommendations have been proposed for the future management of the landslide in order to mitigate potential hazards associated with landslide instability. (c) 2024 China Geology Editorial Office.
引用
收藏
页码:203 / 221
页数:19
相关论文
共 50 条
  • [31] Potential seismic landslide hazard and engineering effect in the Ya'an-Linzhi section of the Sichuan-Tibet transportation corridor, China
    Zhi-hua Yang
    Chang-bao Guo
    Rui-an Wu
    Wei-wei Shao
    Peng-fei Yu
    Cai-hong Li
    China Geology, 2023, (02) : 228 - 240
  • [32] Discussion on the effectiveness of landslide hazard identification and factors affecting the effectiveness of LT-1 satellite based on InSAR technology
    Xiong, Junzhe
    Chen, Tao
    Yang, Guangbin
    Wang, Renru
    Li, Man
    Zhao, Linglin
    Chen, Chunyang
    GEOCARTO INTERNATIONAL, 2025, 40 (01)
  • [33] Potential seismic landslide hazard and engineering effect in the Ya'an-Linzhi section of the Sichuan-Tibet transportation corridor, China
    Yang, Zhi-hua
    Guo, Chang-bao
    Wu, Rui-an
    Shao, Wei-wei
    Yu, Peng-fei
    Li, Cai-hong
    CHINA GEOLOGY, 2023, 6 (02) : 228 - 240
  • [34] Evaluation of Geological Hazard Susceptibility of Baiyin City Based on Multi-temporal InSAR Deformation Measurements
    Ge, Qiaoqiao
    Sun, Qian
    Zhang, Ning
    Hu, Jun
    Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2024, 49 (08): : 1434 - 1443
  • [35] Landslide hazard analysis based on SBAS-InSAR and MCE-CNN model: a case study of Kongtong, Pingliang
    Zhang, Yi
    Chen, Yangyang
    Ming, Dongping
    Zhu, Yueqin
    Ling, Xiao
    Zhang, Xinyi
    Lian, Xinyi
    GEOCARTO INTERNATIONAL, 2022,
  • [36] Deformation Monitoring and Dynamic Analysis of Long-Runout Bedding Landslide Based on InSAR and Particle Flow Code
    Gao, Yang
    Li, Jun
    Liu, Xiaojie
    Wu, Weile
    Zhang, Han
    Liu, Pengfei
    REMOTE SENSING, 2023, 15 (21)
  • [37] Experimental Study on Deformation Monitoring of Large Landslide in Reservoir Area of Hydropower Station Based on GB-InSAR
    Guo, Yanhui
    Yang, Zhiquan
    Yang, Yi
    Kong, Zhijun
    Gao, Caikun
    Tian, Weiming
    ADVANCES IN CIVIL ENGINEERING, 2021, 2021
  • [38] Evolutionary analysis of slope direction deformation in the Gaojiawan landslide based on time-series InSAR and Kalman filtering
    Yao, Jingchuan
    Zhan, Runqing
    Guo, Jiliang
    Wang, Wei
    Yuan, Muce
    Li, Guangyu
    Zhang, Bo
    Zhang, Rui
    PLOS ONE, 2024, 19 (12):
  • [39] Advanced Prediction of Landslide Deformation Through Temporal Fusion Transformer and Multivariate Time-Series Clustering of InSAR: Insights From the Badui Region, Eastern Tibet
    Yang, Yuchuan
    Dou, Jie
    Merghadi, Abdelaziz
    Liang, Wenxin
    Dong, Aonan
    Xiong, Deqing
    Zhang, Lele
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024, 62
  • [40] Frequent Glacial Hazard Deformation Detection Based on POT-SBAS InSAR in the Sedongpu Basin in the Himalayan Region
    Li, Haoliang
    Yang, Yinghui
    Dong, Xiujun
    Xu, Qiang
    Li, Pengfei
    Zhao, Jingjing
    Chen, Qiang
    Hu, Jyr-Ching
    REMOTE SENSING, 2025, 17 (02)