Acta Geodaetica et Cartographica Sinica ›› 2025, Vol. 54 ›› Issue (7): 1178-1191.doi: 10.11947/j.AGCS.2025.20250061

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Wide area coastal subsidence monitoring and driver analysis with multi tracks of TS-InSAR—a case study of Shandong province

Peng LI1,2(), Jianbo BAI1,2(), Zhenhong LI3, Houjie WANG1,2   

  1. 1.Institute of Estuarine and Coastal Zone, College of Marine Geosciences, Ocean University of China, Qingdao 266100, China
    2.Laboratory of Marine Geology, Qingdao Marine Science and Technology Center, Qingdao 266061, China
    3.College of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China
  • Received:2025-02-17 Revised:2025-05-29 Online:2025-08-18 Published:2025-08-18
  • Contact: Jianbo BAI E-mail:pengli@ouc.edu.cn;baijianbo@stu.ouc.edu.cn
  • About author:LI Peng (1984—), male, PhD, associate professor, majors in coastal subsidence monitoring and coastal remote sensing. E-mail: pengli@ouc.edu.cn
  • Supported by:
    Shandong Provincial Natural Science Foundation(ZR2024MD061);The National Natural Science Foundation of China(42041005-4)

Abstract:

Coastal subsidence will exacerbate relative sea level rise and increase the risk of flood-related coastal infrastructure inundation and soil salinization. As a major economic province in the east coast of China, the coastline of Shandong accounts for about 1/6 of the country. However, the spatiotemporal evolution characteristics and key drivers of land subsidence in Shandong are still unclear. In this paper, we conducted multi-track radar interferometry (InSAR) time series analysis with the Sentinel-1 imagery from 2019 to 2022. Firstly, we proposed a multi-track InSAR uncontrolled splice method applicable to the interface region between land and sea to correct the systematic bias of interferograms from adjacent tracks. Then, we generated a large-scale land subsidence rate map of the whole province with good consistency. Furthermore, we found multiple sinking funnels over 50 mm/a. Based on Sentinel-2 multispectral remote sensing images, deformation time series and principal component analysis, we revealed the spatiotemporal change of the heterogeneous sedimentation funnel and its drivers. The results show that human activities related to groundwater pumping and coal mining are the main factors causing land subsidence in Shandong province. This study is expected to provide technical support and scientific basis for large-scale coastal subsidence monitoring and risk management, and further improve the understanding of coastal geological disaster risk.

Key words: coastal subsidence, time-series InSAR, multi-track splicing, Sentinel-1, Sentinel-2, principal component analysis, driving factor, human activities

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