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
  • [21] Detecting Land Subsidence Due to Groundwater Withdrawal in Aliabad Plain, Iran, Using ESA Sentinel-1 Satellite Data
    Edalat, Ali
    Khodaparast, Mahdi
    Rajabi, Ali M.
    NATURAL RESOURCES RESEARCH, 2020, 29 (03) : 1935 - 1950
  • [22] Detecting Land Subsidence Due to Groundwater Withdrawal in Aliabad Plain, Iran, Using ESA Sentinel-1 Satellite Data
    Ali Edalat
    Mahdi Khodaparast
    Ali M. Rajabi
    Natural Resources Research, 2020, 29 : 1935 - 1950
  • [23] DEEP RECURRENT NEURAL NETWORKS FOR LAND-COVER CLASSIFICATION USING SENTINEL-1 INSAR TIME SERIES
    Ge, Shaojia
    Antropov, Oleg
    Su, Weimin
    Gu, Hong
    Praks, Jaan
    2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 473 - 476
  • [24] Estimation, modeling, and prediction of land subsidence using Sentinel-1 time series in Tehran-Shahriar plain: A machine learning-based investigation
    Azarakhsh, Zeinab
    Azadbakht, Mohsen
    Matkan, Aliakbar
    REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2022, 25
  • [25] Crop Classification Based on Temporal Information Using Sentinel-1 SAR Time-Series Data
    Xu, Lu
    Zhang, Hong
    Wang, Chao
    Zhang, Bo
    Liu, Meng
    REMOTE SENSING, 2019, 11 (01)
  • [26] Time series subsidence analysis of drilling solution miningrock salt mines based on Sentinel-1 data and SBAS-InSAR technique
    Xiao L.
    He Y.
    Xing X.
    Wen D.
    Tong C.
    Chen L.
    Yu X.
    Yaogan Xuebao/Journal of Remote Sensing, 2019, 23 (03): : 501 - 513
  • [27] Monitoring of recent ground surface subsidence in the Cangzhou region by the use of the InSAR time-series technique with multi-orbit Sentinel-1 TOPS imagery
    Zhou, Hongyue
    Wang, Yunjia
    Yan, Shiyong
    Li, Yi
    Liu, Xixi
    Zhang, Feiyue
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2018, 39 (22) : 8113 - 8128
  • [28] Evaluation of Using Sentinel-1 and-2 Time-Series to Identify Winter Land Use in Agricultural Landscapes
    Denize, Julien
    Hubert-Moy, Laurence
    Betbeder, Julie
    Corgne, Samuel
    Baudry, Jacques
    Pottier, Eric
    REMOTE SENSING, 2019, 11 (01)
  • [29] Paddy Rice Mapping in Thailand Using Time-Series Sentinel-1 Data and Deep Learning Model
    Xu, Lu
    Zhang, Hong
    Wang, Chao
    Wei, Sisi
    Zhang, Bo
    Wu, Fan
    Tang, Yixian
    REMOTE SENSING, 2021, 13 (19)
  • [30] An approach for multi-dimensional land subsidence velocity estimation using time-series Sentinel-1 SAR datasets by applying persistent scatterer interferometry technique
    Awasthi, Shubham
    Jain, Kamal
    Mishra, Vishal
    Kumar, Ajeet
    GEOCARTO INTERNATIONAL, 2022, 37 (09) : 2647 - 2678