Volume 9 Issue 2
May  2020
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Article Navigation >  Journal of Radars  > 2020  >  9(2): 277-294
WU Songbo, LE Yongyao, ZHANG Lei, et al. Multi-temporal InSAR for urban deformation monitoring: Progress and challenges[J]. Journal of Radars, 2020, 9(2): 277–294. DOI: 10.12000/JR20037
Citation: WU Songbo, LE Yongyao, ZHANG Lei, et al. Multi-temporal InSAR for urban deformation monitoring: Progress and challenges[J]. Journal of Radars, 2020, 9(2): 277–294. DOI: 10.12000/JR20037
shu

Multi-temporal InSAR for Urban Deformation Monitoring: Progress and Challenges (in English)

DOI: 10.12000/JR20037
  • 1.

    Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, KLN, Hong Kong 999077, China

  • 2.

    Xi’an Engineering Investigation and Design Research Institute of China National Nonferrous Metals Industry Co. Ltd., Xi’an 710000, China

Funds:  The National Natural Science Foundation of China (41774023), The Research Grants Council (RGC) of Hong Kong (PolyU152232/17E, PolyU152164/18E), The Faculty of Construction and Environment (ZZGD), The Research Institute for Sustainable Urban Development (RISUD) (1-BBWB), The TerraSAR-X Science plan (GEO3603)
More Information
  • Author Bio:

    WU Songbo was born in Xinjiang, China, in 1990. He received M.Sc. from South-West Jiaotong University, China, in 2015. He is currently working towards his Ph.D. in the Department of Land Surveying and Geo-Informatics (LSGI), The Hong Kong Polytechnic University, Hong Kong. His research interests include development of advanced processing algorithms for MT-InSAR and continuous ground deformation monitoring. E-mail: sabriwu@outlook.com

    ZHANG Lei was born in Yantai, China, in 1981. He received M.Sc. from Tongji University, Shanghai, China, in 2007 and Ph.D. from The Hong Kong Polytechnic University, Hong Kong, in 2011. He has since then been a Research Assistant Professor in the Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University. His current research interests include developing advanced processing techniques for SAR data and application of the technology to study natural hazards. E-mail: lslzhang@ieee.org

    DING Xiaoli received B.Eng. from Central South University of Metallurgy, Changsha, China, in 1983 and Ph.D. from the University of Sydney, Australia, in 1993. He is currently Chair Professor of Geomatics in Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong. He lectured at the Northeast University of Technology, Shenyang, China (in 1983–1986), and Curtin University of Technology, Perth, Australia (in 1992–1996), before joining The Hong Kong Polytechnic University in 1996. His main research interests are in developing technologies for studying ground and structural deformation and geohazards. E-mail: xl.ding@polyu.edu.hk

  • Corresponding author: DING Xiaoli, xl.ding@polyu.edu.hk
  • Received Date: 2020-04-08
  • Rev Recd Date: 2020-04-21
    • Available Online: 2020-05-09
  • Publish Date: 2020-04-01
    Abstract

  • Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) is one of the most powerful Earth observation techniques, especially useful for measuring highly detailed ground deformation over large ground areas. Much research has been carried out to apply MT-InSAR to monitor ground and infrastructure deformation in urban areas related to land reclamation, underground construction and groundwater extraction. This paper reviews the progress in the research and identifies challenges in applying the technology, including the inconsistency in coherent point identification when different approaches are used, the reliability issue in parameter estimation, difficulty in accurate geolocation of measured points, the one-dimensional line-of-sight nature of InSAR measurements, the inability of making complete measurements over an area due to geometric distortions, especially the shadowing effects, the challenges in processing large SAR datasets, the decrease of the number of coherent points with the increase of the length of SAR time series, and the difficulty in quality control of MT-InSAR results.

     

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