Abstract
Abnormal surface subsidence has become a widespread geological problem being faced by cities. As a first-tier city in the world, there are problems such as unclear analysis of subsidence mechanism. Therefore, the monitoring of the Shanghai surface is particularly important. In this paper, the Sentinel-1A satellite SAR image data of 36 scenes covering Shanghai area from January 2018 to March 2020 were processed on the basis of time-series interferometry synthetic aperture radar technique. The subsidence rate field and accumulated surface subsidence in Shanghai area during the study period were obtained, and the spatial–temporal distribution characteristics of subsidence in the study area were discussed and analyzed from many different aspects. Moreover, the correlation between regional subsidence and geological structure, precipitation, urbanization, and other influencing factors were analyzed and established. Results show that the non-uniform subsidence in Shanghai area is clear, and those of the districts of eastern Songjiang, southern Jinshan, and Fengxian are more serious with a maximum subsidence rate of −26.2 mm/year. After analyzing the causes of subsidence, the special foundation of soft soil in Shanghai area is determined as the main reason for the subsidence, and the uneven subsidence is mainly caused by the over-exploitation of groundwater, human activities, and the subsidence of soil layer. Through comparative analysis, factors, such as rainfall, groundwater, and urbanization process, have high correlation with surface subsidence.
Highlights
As a serious geological disaster, surface subsidence will directly lead to major safety accidents, such as the collapsing of grounds and houses, which seriously threatens the safety of human life and property [1,2]
Aiming at the problems of interference incoherence and atmospheric delay error that exists in differential interferometry synthetic aperture radar (DInSAR) technique, persistent scatterer InSAR (PSInSAR) technique can reduce the influence of interference incoherence and atmospheric delay error on the calculation results effectively
Sci. 2021, 11, x FOR PEER REVIvEaWlues indicate surface uplift, and the negative values represents surface subsidence8), oafn2d2 the map is superimposed on a Google Earth image of Shanghai acquired in 2020
Summary
As a serious geological disaster, surface subsidence will directly lead to major safety accidents, such as the collapsing of grounds and houses, which seriously threatens the safety of human life and property [1,2]. Calof et al [22] analyzed the driving factors of surface deformation in Kongya area by using SBASInSAR technique and combining the data of climate, strata, and land cover change. Qin et al [30] used PSInSAR technique to monitor the main traffic infrastructure in Shanghai area and compared with the level data. They found that some traffic lines in Shanghai had serious subsidence and verified the feasibility of PSInSAR in subsidence monitoring in Shghai area. The driving factors of subsidence were analyzed in combination with urbanization construction, groundwater level change, rainfall, and other factors in Shanghai These factors provide scientific data support for the surface subsidence prevention and control in Shanghai area
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