Monitoring city subsidence by D-InSAR in Tianjin area

被引:0
|
作者
Tao, L [1 ]
Liu, JN [1 ]
Liao, MS [1 ]
Kuang, SJ [1 ]
Lu, X [1 ]
机构
[1] Wuhan Univ, GPS Engn Res Ctr, Wuhan, Peoples R China
关键词
component; city subsidence; D-InSAR; temporal decorrelation; ground water;
D O I
暂无
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Recently D-InSAR technique has been widely adopted to monitor land subsidence caused by withdrawal of water, oil, gas, and other minerals. Though many cities in China have seriously suffered from land subsidence caused by ground water over-extracting, few of them have enough money to do the leveling control of the subsidence. Compared with leveling and GPS surveying, D-InSAR is more cost-efficient and precise. As Tianjin city has scores of ERS-1/2 SAR data, thousands of valuable leveling data, smooth topography and severe subsidence, it is an ideal place to test and analyze D-InSAR technique. However. D-InSAR is liable to he contaminated by atmosphere delay, temporal decorrelation and baseline errors. As these errors cannot be removed by SAR data processing, some auxiliary data such as leveling data and DEM data have been introduced into D-InSAR data processing. Therefore, this paper accurately analyzes the features of atmosphere delay and temporal decorrelation with the auxiliary data in Tianjin urban area. The results demonstrate that D-InSAR can detect subsidence within three months. Further actions will be undertaken to improve the D-InSAR subsidence monitoring system, such as using Envisat data, gathering GPS zenith delay data to eliminate the atmosphere delay, and so on. The ultimate interest of our research is to establish a robust, cost efficient city subsidence monitoring system by using D-InSAR technique an other measurement.
引用
收藏
页码:3333 / 3336
页数:4
相关论文
共 50 条
  • [31] D-InSAR Monitoring Method of Mining Subsidence Based on Boltzmann and Its Application in Building Mining Damage Assessment
    Lei Wang
    Chaoqun Teng
    Kegui Jiang
    Chuang Jiang
    Shangjun Zhu
    [J]. KSCE Journal of Civil Engineering, 2022, 26 : 353 - 370
  • [32] D-InSAR Monitoring Method of Mining Subsidence Based on Boltzmann and Its Application in Building Mining Damage Assessment
    Wang, Lei
    Teng, Chaoqun
    Jiang, Kegui
    Jiang, Chuang
    Zhu, Shangjun
    [J]. KSCE JOURNAL OF CIVIL ENGINEERING, 2022, 26 (01) : 353 - 370
  • [33] A Dynamic Prediction Method of Deep Mining Subsidence Combines D-InSAR Technique
    Wang XunChun
    Zhang Yue
    Jiang XingGe
    Zhang Peng
    [J]. 2011 3RD INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND INFORMATION APPLICATION TECHNOLOGY ESIAT 2011, VOL 10, PT C, 2011, 10 : 2533 - 2539
  • [34] A study of mining-induced subsidence in Hebi coalfield based on D-InSAR
    Chao, Ma
    [J]. LAND SURFACE REMOTE SENSING II, 2014, 9260
  • [35] Landslide Displacement Monitoring Using Multi-aperture InSAR and D-InSAR
    He, Liming
    Wu, Lixin
    Liu, Shanjun
    Su, Chang
    [J]. PIERS 2014 GUANGZHOU: PROGRESS IN ELECTROMAGNETICS RESEARCH SYMPOSIUM, 2014, : 1416 - 1419
  • [36] Deformation Monitoring and Spatiotemporal Evolution of Mining Area with Unmanned Aerial Vehicle and D-InSAR Technology
    Tan, Hao
    Yu, Xuexiang
    Zhu, Mingfei
    Guo, Zhongchen
    Chen, Hengzhi
    [J]. MOBILE INFORMATION SYSTEMS, 2022, 2022
  • [37] Urban subsidence observed by InSAR in Tianjin region
    Zhang Shiyu
    Li Tao
    Liu Jingnan
    Liu Youwen
    Shao Lianjun
    Xia Ye
    [J]. IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, : 2078 - +
  • [38] Monitoring the Land Subsidence Area in a Coastal Urban Area with InSAR and GNSS
    Hu, Bo
    Chen, Junyu
    Zhang, Xingfu
    [J]. SENSORS, 2019, 19 (14)
  • [39] APPLICATION OF D-INSAR TECHNOLOGY ON RISK ASSESSMENT OF MINING AREA
    Zhang, Zhiliang
    Zeng, Qiming
    Jiao, Jian
    [J]. 2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 9695 - 9698
  • [40] Dynamic prediction model of mining subsidence combined with D-InSAR technical parameter inversion
    Hou, Zhixian
    Yang, Keming
    Li, Yanru
    Gao, Wei
    Wang, Shuang
    Ding, Xinming
    Li, Yaxing
    [J]. ENVIRONMENTAL EARTH SCIENCES, 2022, 81 (11)