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The monitoring and analysis of the coastal lowland subsidence in the southern Hangzhou Bay with an advanced time-series InSAR method

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Abstract

Time-series InSAR analysis (e.g., permanent scatterers (PSInSAR)) has been proven as an effective technology in monitoring ground deformation over urban areas. However, it is a big challenge to apply this technology in coastal regions due to the lack of man-made targets. An distributed scatterers interferometric synthetic aperture radar (DSInSAR) is developed to solve the problem of insufficient samples and low reliability in monitoring coastal lowland subsidence, by applying a spatially adaptive filter and an eigendecomposition algorithm to estimating the optimal phase of statistically homogeneous distributed scatterers (DSs). Twenty-four scenes of COSMO-SkyMed images acquired between 2013 and 2015 are used to retrieve the land subsidence over the Shangyu District on south coast of the Hangzhou Bay, Zhejiang Province, China. The spatial pattern of the land subsidence obtained by the PS-InSAR and the DSInSAR coincides with each other, but the density of the DSs is three point five times higher than the permanent scatterers (PSs). Validated by precise levelling data over the same period, the DSInSAR method achieves an accuracy of ±5.0 mm/a which is superior to the PS-InSAR with ±5.5 mm/a. The land subsidence in the Shangyu District is mainly distributed in the urban areas, industrial towns and land reclamation zones, with a maximum subsidence rate–30.2 mm/a. The analysis of geological data, field investigation and historical reclamation data indicates that human activities and natural compaction of reclamation material are major causes of the detected land subsidence. The results demonstrate that the DSInSAR method has a great potential in monitoring the coastal lowland subsidence and can be used to further investigate subsidence-related environmental issues in coastal regions.

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Authors and Affiliations

  1. Administrative Center for China’s Agenda 21, Beijing, 100038, China

    Peng Han

  2. College of Earth Science, Chengdu University of Technology, Chengdu, 610059, China

    Xiaoxia Yang

  3. Key Laboratory of Geoscience Spatial Information Technology of Ministry of Land and Resources, Chengdu University of Technology, Chengdu, 610059, China

    Xiaoxia Yang

  4. College of Earth Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China

    Lin Bai & Qishi Sun

Authors
  1. Peng Han
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  2. Xiaoxia Yang
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  3. Lin Bai
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  4. Qishi Sun
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Correspondence to Xiaoxia Yang.

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Han, P., Yang, X., Bai, L. et al. The monitoring and analysis of the coastal lowland subsidence in the southern Hangzhou Bay with an advanced time-series InSAR method. Acta Oceanol. Sin. 36, 110–118 (2017). https://doi.org/10.1007/s13131-017-1087-y

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  • DOI: https://doi.org/10.1007/s13131-017-1087-y

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