Investigation of land subsidence in Guangdong Province, China, using PS-InSAR technique

被引:0
|
作者
Uang, Liangke [1 ,2 ]
Zhu, Peijie [1 ]
Zha, Tengxu [3 ,4 ]
He, Lin [3 ]
Wu, Wenhao [5 ]
Ge, Zixuan [5 ]
Ai, Hui [5 ]
机构
[1] Guilin Univ Technol, Coll Geomat & Geoinformat, Guilin 541004, Peoples R China
[2] Guangxi Key Lab Spatial Informat & Geomat, Guilin, Peoples R China
[3] Hubei Univ Sci & Technol, Res Ctr Beidou Ind Dev Key Res Inst Humanities & S, Coll Resources & Environm Sci & Engn, Xianning 437100, Peoples R China
[4] Wuhan Gravitat & Solid Earth Tides Natl Observat &, Wuhan 430071, Hubei, Peoples R China
[5] Hunan Univ Sci & Technol, Sch Earth Sci & Spatial Informat Engn, Xiangtan 411201, Peoples R China
基金
中国国家自然科学基金;
关键词
Ground subsidence; Sentinel-1A; PS-InSAR; Seasonal fluctuations; Guangzhou and Foshan; SYNTHETIC-APERTURE RADAR; GROUND SUBSIDENCE; FIELD; DEFORMATION; CALIFORNIA; VALLEY;
D O I
10.1016/j.asr.2024.12.034
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Ground subsidence is a natural disaster that can cause severe consequences such as surface deformation and building collapse. With rapid economic growth, activities such as groundwater extraction, subway construction, and large-scale infrastructure projects have weakened the soil's load-bearing capacity, resulting in subsidence issues for buildings and the ground. As the mechanism of land subsidence caused by the above factors is still unclear, it is necessary to conduct further study in a specific area. Intending to provide a scientific basis for successfully preventing and mitigating the potential risks associated with subsidence, we employed the Persistent Scatterer InSAR (PS-InSAR) technique for monitoring to precisely explore the causes, processes, and impacts of the subsidence. In this study, 14 Sentinel-1A terrain observations by progressive scans (TOPS) Synthetic Aperture Radar (SAR) images from January to December 2020 have been selected to investigate the spatiotemporal ground deformation in the specific Guangzhou and Foshan regions. Various analytical methods have been employed to investigate the significant deformation mechanism. Firstly, we analyzed characteristic points in industrial parks and urban areas. Subsequently, detailed investigations were conducted in three severely subsiding areas: Huadu, Nanhai, and Haizhu districts. Results demonstrate that the region's surface deformation is highly heterogeneous; subsidence is primarily concentrated in urban areas and usually spreads outward from city centers. Additionally, numerous uplift regions were identified, with the maximum uplift rate exceeding 29 mm/yr. In particular, the highest rates of subsidence were found in Guangzhou's Haizhu District, with annual average rates ranging from 28.3 mm/yr to 29.4 mm/yr, and significant seasonal fluctuations of nonlinear subsidence patterns have also been detected. Furthermore, comparative analysis of factors such as urban development (e.g., subway systems and artificial structures), rainfall, and industrial expansion in major subsidence areas indicates that subsidence in this region is primarily influenced by anthropogenic factors (such as industrial development and surface loading) as well as natural factors like rainfall and karst processes. (c) 2024 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:3507 / 3520
页数:14
相关论文
共 50 条
  • [31] Land Deformation Monitoring Using PS-InSAR Technique Over Sahel-Doukkala (Morocco)
    Habib, Adnane
    Labbassi, Kamal
    Delgado Blasco, Jose Manuel
    van Leijen, Freek
    Iannini, Lorenzo
    Menenti, Massimo
    2017 3RD INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR SIGNAL AND IMAGE PROCESSING (ATSIP), 2017, : 73 - +
  • [32] PS-InSAR Based Monitoring of Land Subsidence by Groundwater Extraction for Lahore Metropolitan City, Pakistan
    Hussain, Muhammad Afaq
    Chen, Zhanlong
    Zheng, Ying
    Shoaib, Muhammad
    Ma, Junwei
    Ahmad, Ijaz
    Asghar, Aamir
    Khan, Junaid
    REMOTE SENSING, 2022, 14 (16)
  • [33] Ground instability detection using PS-InSAR in Lanzhou, China
    Zeng, R. Q.
    Meng, X. M.
    Wasowski, J.
    Dijkstra, T.
    Bovenga, F.
    Xue, Y. T.
    Wang, S. Y.
    QUARTERLY JOURNAL OF ENGINEERING GEOLOGY AND HYDROGEOLOGY, 2014, 47 (04) : 307 - 321
  • [34] Land subsidence susceptibility mapping in urban settlements using time-series PS-InSAR and random forest model
    Zhao, Fancheng
    Miao, Fasheng
    Wu, Yiping
    Xiong, Yuan
    Gong, Shunqi
    Sun, Dingkun
    GONDWANA RESEARCH, 2024, 125 : 406 - 424
  • [35] Beijing Land Subsidence Revealed Using PS-InSAR with Long Time Series TerraSAR-X SAR Data
    Bai, Zechao
    Wang, Yanping
    Balz, Timo
    REMOTE SENSING, 2022, 14 (11)
  • [36] Multi-Scale Analysis of the Relationship between Land Subsidence and Buildings: A Case Study in an Eastern Beijing Urban Area Using the PS-InSAR Technique
    Yang, Qin
    Ke, Yinghai
    Zhang, Dongyi
    Chen, Beibei
    Gong, Huili
    Lv, Mingyuan
    Zhu, Lin
    Li, Xiaojuan
    REMOTE SENSING, 2018, 10 (07):
  • [37] Monitoring of Subsidence Over a Continuous Miner-Based Coal Mine Caving Panels Using PS-InSAR Technique
    Anil, J.
    Kumar, Kapil
    Ram, Sahendra
    Chatterjee, S.
    Gorai, A. K.
    MINING METALLURGY & EXPLORATION, 2023, 40 (02) : 719 - 736
  • [38] Land Subsidence Monitoring Method in Regions of Variable Radar Reflection Characteristics by Integrating PS-InSAR and SBAS-InSAR Techniques
    Zhang, Peng
    Guo, Zihao
    Guo, Shuangfeng
    Xia, Jin
    REMOTE SENSING, 2022, 14 (14)
  • [39] Monitoring of Subsidence Over a Continuous Miner-Based Coal Mine Caving Panels Using PS-InSAR Technique
    J. Anil
    Kapil Kumar
    Sahendra Ram
    S. Chatterjee
    A. K. Gorai
    Mining, Metallurgy & Exploration, 2023, 40 : 719 - 736
  • [40] Estimation of ground subsidence of New Delhi, India using PS-InSAR technique and Multi-sensor Radar data
    Malik, Kapil
    Kumar, Dheeraj
    Perissin, Daniele
    Pradhan, Biswajeet
    ADVANCES IN SPACE RESEARCH, 2022, 69 (04) : 1863 - 1882