Understanding the Spatiotemporal Characteristics of Land Subsidence and Rebound in the Lianjiang Plain Using Time-Series InSAR with Dual-Track Sentinel-1 Data

被引:2
|
作者
He, Yangfan [1 ]
Ng, Alex Hay-Man [1 ,2 ]
Wang, Hua [3 ]
Kuang, Jianming [4 ]
机构
[1] Guangdong Univ Technol, Dept Surveying Engn, Guangzhou 510006, Peoples R China
[2] Guangdong Univ Technol, Key Lab City Cluster Environm Safety & Green Dev, Minist Educ, Guangzhou 510006, Peoples R China
[3] South China Agr Univ, Coll Nat Resources & Environm, Guangzhou 510642, Peoples R China
[4] Univ New South Wales UNSW, Sch Civil & Environm Engn, Sydney, NSW 2052, Australia
基金
中国国家自然科学基金;
关键词
land displacement; time-series InSAR; groundwater level; Lianjiang Plain; GROUND DEFORMATION; RADAR INTERFEROMETRY; BASIN; RESOLUTION; VALLEY;
D O I
10.3390/rs15133236
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Lianjiang Plain, renowned for its position as 'China's textile hub' and characterized by its high population density, has experienced considerable subsidence due to excessive groundwater extraction in recent years. Although some studies have investigated short-term subsidence in this plain, research on long-term subsidence and rebound remain understudied. In this paper, the characteristics of surface deformation in the Lijiang Plain during two periods (2015-2017 and 2018-2021) have been investigated using the time-series interferometric synthetic aperture radar (TS-InSAR) technique, and the correlation with the changes in groundwater level, geological factors, and urban construction are discussed. The InSAR-derived results are cross-validated with the adjacent orbit datasets. Large-scale and uneven subsidence ranging from -124 mm/year to +40 mm/year is observed from 2015 to 2017. However, a significant decrease in the subsidence rate during 2018-2021, with local rebound deformation up to +48 mm/year in three regions, is also observed. Groundwater level changes are found to be the major cause of the ground deformation, and the intercomparison between groundwater level and ground displacement time series from TS-InSAR measurements also indicates a clear relationship between them during 2018-2021. Geological factors control the range of deformation area over the study period. The impact of urban construction on surface subsidence is evident, contributing to high deformation. Our findings could improve the understanding of how deformation is affected by groundwater rebound and offer valuable insights into groundwater management, urban planning, and land subsidence mitigation.
引用
收藏
页数:17
相关论文
共 50 条
  • [31] Time-Series InSAR Monitoring of Permafrost Freeze-Thaw Seasonal Displacement over Qinghai-Tibetan Plateau Using Sentinel-1 Data
    Zhang, Xuefei
    Zhang, Hong
    Wang, Chao
    Tang, Yixian
    Zhang, Bo
    Wu, Fan
    Wang, Jing
    Zhang, Zhengjia
    REMOTE SENSING, 2019, 11 (09)
  • [32] Wet snow detection using dual-polarized Sentinel-1 SAR time series data considering different land categories
    Liu, Chang
    Li, Zhen
    Zhang, Ping
    Huang, Lei
    Li, Zhixian
    Gao, Shuo
    GEOCARTO INTERNATIONAL, 2022, 37 (25) : 10907 - 10924
  • [33] Land Cover Mapping Using Sentinel-1 Time-Series Data and Machine-Learning Classifiers in Agricultural Sub-Saharan Landscape
    Dahhani, Sara
    Raji, Mohamed
    Hakdaoui, Mustapha
    Lhissou, Rachid
    REMOTE SENSING, 2023, 15 (01)
  • [34] Hierarchical classification for improving parcel-scale crop mapping using time-series Sentinel-1 data
    Zhou, Ya'nan
    Zhu, Weiwei
    Li, Feng
    Gao, Jianwei
    Chen, Yuehong
    Xin, Zhang
    Luo, Jiancheng
    JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2024, 369
  • [35] Paddy Rice Mapping in Hainan Island Using Time-Series Sentinel-1 SAR Data and Deep Learning
    Shen, Guozhuang
    Liao, Jingjuan
    REMOTE SENSING, 2025, 17 (06)
  • [36] Analyzing urbanization induced groundwater stress and land deformation using time-series Sentinel-1 datasets applying PSInSAR approach
    Awasthi, Shubham
    Jain, Kamal
    Bhattacharjee, Sutapa
    Gupta, Vivek
    Varade, Divyesh
    Singh, Hemant
    Narayan, Avadh Bihari
    Budillon, Alessandra
    SCIENCE OF THE TOTAL ENVIRONMENT, 2022, 844
  • [37] Land Subsidence Susceptibility Mapping in Jakarta Using Functional and Meta-Ensemble Machine Learning Algorithm Based on Time-Series InSAR Data
    Hakim, Wahyu Luqmanul
    Achmad, Arief Rizqiyanto
    Lee, Chang-Wook
    REMOTE SENSING, 2020, 12 (21) : 1 - 26
  • [38] Crop Classification and Representative Crop Rotation Identifying Using Statistical Features of Time-Series Sentinel-1 GRD Data
    Zhou, Xin
    Wang, Jinfei
    He, Yongjun
    Shan, Bo
    REMOTE SENSING, 2022, 14 (20)
  • [39] Combining Time-Series Variation Modeling and Fuzzy Spatiotemporal Feature Fusion: A Novel Approach for Unsupervised Flood Mapping Using Dual-Polarized Sentinel-1 SAR Images
    Li, Congyu
    Liu, Jiaqi
    Liu, Xinxin
    Kang, Xudong
    Li, Shutao
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 61
  • [40] Characterizing Time-Series Roving Artisanal and Small-Scale Gold Mining Activities in Indonesia Using Sentinel-1 Data
    Kimijima, Satomi
    Sakakibara, Masayuki
    Nagai, Masahiko
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (10)