PS-InSAR-based monitoring and analysis of surface subsidence in Shanghai

ZHANG Zhihua; HU Changtao; ZHANG Zhen; YANG Shuwen

doi:10.6046/zrzyyg.2021291

2022 Vol. 34, No. 3

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ZHANG Zhihua, HU Changtao, ZHANG Zhen, YANG Shuwen. 2022. PS-InSAR-based monitoring and analysis of surface subsidence in Shanghai. Remote Sensing for Natural Resources, 34(3): 106-111. doi: 10.6046/zrzyyg.2021291

Citation:

ZHANG Zhihua, HU Changtao, ZHANG Zhen, YANG Shuwen. 2022. PS-InSAR-based monitoring and analysis of surface subsidence in Shanghai. Remote Sensing for Natural Resources, 34(3): 106-111. doi: 10.6046/zrzyyg.2021291

PS-InSAR-based monitoring and analysis of surface subsidence in Shanghai

1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China；
2. National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China；
3. Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China

Received Date: 13 September 2021

Revised Date: 15 September 2022

Publish Date: 21 September 2022

Abstract

Abstract

Urban surface subsidence has increasingly severe impacts on human life, making it particularly important to study the methods for effectively monitoring surface subsidence. To monitor the surface subsidence in Shanghai, this study processed 24 scenes of 2019—2020 Sentinel-1A data covering the city using the PS-InSAR technique. After treatment using the permanent scatterer interferometry technique, the residual phase correction was performed using SRTM1 DEM, and the surface subsidence results of the two years were extracted. The analysis of the subsidence rate and cumulative subsidence amplitude in the monitoring results shows that the urban area mainly shows uneven surface subsidence with multiple subsidence funnels, some of which correspond to the historical subsidence data. As shown by time-series surface subsidence data of seldomly selected ground characteristic points, the surface subsidence at these points basically had the same deformation amplitude at different times and highly consistent changing trends, verifying the reliability of the PS-InSAR monitoring method. The results of this study will provide data and decision-making bases for geologic disaster prevention and control in Shanghai.
- surface subsidence /
- InSAR /
- PS-InSAR /
- Shanghai

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References

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