Land subsidence monitoring based on InSAR and inversion of aquifer parameters

被引:0
|
作者
Zhang Ziwen
Yijun Liu
Feng Li
Qi Li
Wujian Ye
机构
[1] Guangdong University of Technology,School of Information Engineering
[2] Guangdong Polytechnic Normal University,School of Automobile and Transportation Engineering
关键词
InSAR; CWT; Parameter inversion; Groundwater; Subsidence;
D O I
暂无
中图分类号
学科分类号
摘要
In order to accurately separate the elastic and inelastic deformation information caused by aquifer compression in the land subsidence signal, and to invert the hydrogeological parameters of high spatial and temporal resolution to better apply the groundwater-ground subsidence model, a CWT (Continuous Wavelet Transform) separation method for aquifer elastic and inelastic deformation signals based on CWT is adopted, and the deformation signal is extracted by InSAR technology. The large-scale synthetic aperture radar dataset obtained by Envisat satellite from 2007 to 2009 is collected to obtain the surface deformation characteristic of the area by SBAS-InSAR technology, and then the independence provided by the observation well is used. Using the independent water level data provided by the observation wells, combined with the vertical InSAR deformation component and the head data, the CWT method is used to separate the periodic deformation signal components and long-term trends. Finally, the isolated signal component is used to invert the elastic and inelastic storage coefficient based on the ground subsidence model. The settlement signal separation method used in this paper makes up for the shortcomings of the two kinds of information in the previous settlement signal that are difficult to separate, which allows for more accurate inversion of aquifer parameters and helps to understand the aquifer parameters and continuously manage groundwater resources.
引用
收藏
相关论文
共 50 条
  • [21] Monitoring land subsidence in Suzhou city using D-InSAR technique
    Wang Zhiyong
    Zhang Jixian
    Huang Guoman
    Zhang Yonghong
    PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9, 2009, : 2956 - 2959
  • [22] 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)
  • [23] Land Subsidence in a Coastal City Based on SBAS-InSAR Monitoring: A Case Study of Zhuhai, China
    Sun, Huimin
    Peng, Hongxia
    Zeng, Min
    Wang, Simiao
    Pan, Yujie
    Pi, Pengcheng
    Xue, Zixuan
    Zhao, Xinwen
    Zhang, Ao
    Liu, Fengmei
    REMOTE SENSING, 2023, 15 (09)
  • [24] Time series land subsidence monitoring and prediction based on SBAS-InSAR and GeoTemporal transformer model
    Zhang, Jiayi
    Gao, Jian
    Gao, Fanzong
    EARTH SCIENCE INFORMATICS, 2024, 17 (06) : 5899 - 5911
  • [25] Study on monitoring land subsidence in mining city based on coherent target small-baseline InSAR
    College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
    不详
    不详
    Meitan Xuebao, 10 (1606-1611):
  • [26] Mine subsidence monitoring by differential InSAR
    Dong, Yusen
    Ge, Linlin
    Chang, Hsingchun
    Zhang, Zhi
    Geomatics and Information Science of Wuhan University, 2007, 32 (10) : 888 - 891
  • [27] Development and Comparison of InSAR-Based Land Subsidence Prediction Models
    Zheng, Lianjing
    Wang, Qing
    Cao, Chen
    Shan, Bo
    Jin, Tie
    Zhu, Kuanxing
    Li, Zongzheng
    REMOTE SENSING, 2024, 16 (17)
  • [28] Mapping and Analyses of Land Subsidence in Hengshui, China, Based on InSAR Observations
    Li, Man
    Ge, Daqing
    Guo, Xiaofang
    Zhang, Ling
    Liu, Bin
    Wang, Yan
    Wu, Qiong
    Wan, Xiangxing
    Wang, Yu
    LAND, 2023, 12 (09)
  • [29] Sequential InSAR Time Series Deformation Monitoring of Land Subsidence and Rebound in Xi'an, China
    Wang, Baohang
    Zhao, Chaoying
    Zhang, Qin
    Peng, Mimi
    REMOTE SENSING, 2019, 11 (23)
  • [30] THE CORRELATION ANALYSIS OF SUBSIDENCE MONITORING BY D-INSAR AND THE CHANGE OF URBAN CONSTRUCTION LAND
    Yang, KaiJun
    Jiang, Xing Xiang
    Cao, Li
    Lei, Fan
    Zeng, Haibo
    Zhang, Zhe
    ISPRS HANNOVER WORKSHOP: HRIGI 17 - CMRT 17 - ISA 17 - EUROCOW 17, 2017, 42-1 (W1): : 311 - 315