###### Abstract  
Ahnormal 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 Fengian 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. time-series InSAR; surface deformation; Shanghai area; spatial-temporal characteristics; Sentinel-1A +
Footnote †: journal: Applied  
In the 1960s, interferometry synthetic aperture radar (InSAR) technique achieved rapid development. This technique has been widely used in mine subsidence [12], volcano monitoring [13], landslide monitoring [14], earthquake [15], dam [16], and other aspects by virtue of its all-day, all-weather, and wide coverage. With the development of InSAR technique, differential interferometry synthetic aperture radar (DInSAR) technique was introduced. In 1989, [PERSON] et al. [17] obtained the surface displacement of the Impirale Valley, California, USA by using DInSAR technique. However, this technique still has shortcomings (e.g., incoherence and atmospheric delay) that will directly lead to large errors in monitoring results. To solve the shortcomings of DInSAR, several time-series InSAR techniques have been proposed. In 2000, [PERSON] et al. [18] proposed a persistent scatterer InSAR (PSInSAR) technique that works by calculating some persistent scatterer (PS) points during the study period. Then, the influence of atmospheric effect and incoherent factors is reduced. Unlike PSInSAR, the technique proposed by [PERSON] [19] in 2002, which was called small baseline subset InSAR (SBASInSAR), changed the point target modeling method into distributed target modeling analysis. In recent years, with the development of time-series InSAR technique, various time-series InSAR technologies (e.g., MTInSAR [20], TCPInSAR [21]) have emerged, and these time-series InSAR technologies all have good application prospect in surface subsidence monitoring. For example, [PERSON] 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. [PERSON] et al. [23] used SBASInSAR to investigate wide-area surface subsidence characteristics in Wuhan and analyzed and established the correlations between surface subsidence and urban construction, precipitation, industrial development, carbonate karstification, and water level changes in Yangtze River in Wuhan. [PERSON] et al. [24] used ENVISAT ASAR and RADARSAT-2 data to detect obvious subsidence in the northwest of Ciudad Guzman. After field investigation, the feasibility of multi-temporal InSAR technique in surface subsidence was verified.