# Ground Subsidence Analysis in Tianjin (China) Based on Sentinel-1A Data Using MT-InSAR Methods
## 1 Introduction  
Land subsidence is a geological hazard due to natural and human factors [1; 2], such as settlement of loose sediments, compression of unconsolidated strata and overexploitation of underground resources. It is usually a slow process and not easy to be noticed in the early stage. Once the subsidence continues to develop, it could cause the slow lowering of ground surface elevation [3], resulting in critical infrastructures damage [4]. Today, land subsidence has become a global problem and cases of subsidence have been detected in many places all over the world [1]. A number of cities like Mexico [5], Tianjin [6], Jakarta [7], Tokyo [8] and Venice [9] are facing the problem of land subsidence. Traditional land subsidence monitoring methods include global navigation satellite system (GNSS), GPS, leveling, extensometer and geophysical investigation [10]. However, these means arenot only high-cost and laborious, but also generally restricted to a small spatial extent, failing to depict a spatial display of ground subsidence [10]. Interferometric synthetic aperture radar (InSAR) is a confirmed remote sensing method, making use of SAR images' phase information to monitor ground surface displacement. The standard differential interferometry SAR (D-InSAR) method can obtain qualitative information on the displacement from two interferograms. Nevertheless, there are intrinsic shortcomings that could limit its operational capability, such as aerial disturbance, temporal decorrelation and imprecision of the reference DEM [11]. To get over the limitations of D-InSAR, multi-temporal InSAR (MT-InSAR) was proposed in the early 21 st century for mapping ground subsidence with high spatial and temporal resolution [12]. Persistent scatterer InSAR (PS-InSAR) [13] and small baseline subset (SBAS) [14] are the two most widely utilized InSAR time series means. In addition to them, other MT-InSAR approaches developed in recent years, including along track interferometry (ATI) [15], coherent pixels technique (CPT) [16], corner reflector interferometry SAR (CRInSAR) [17] and quasi-PS [18] to reduce decorrelations by combining numerous SAR images. Taking advantage of a set of pixels, the MT-InSAR technique can get the surface displacement history and the corresponding mean displacement rate [19]. By measuring the subsidence area and velocity, the MT-InSAR technique can not only get the early signal of geological hazards which is helpful for forecasting potential events, but can also monitor the trend of ground subsidence, allowing to detect the law of its change [20]. At present, the efficiency and precision of the MT-InSAR technique has been proven in many applications, especially in monitoring ground subsidence. Using the distributed scatterers InSAR method, [PERSON] et al. [21] analyzed the land subsidence based on COSMO-SkyMed images over the coast of Hangzhou Bay, with an area of 1400 km\({}^{2}\), proving the MT-InSAR technique achieves an accuracy of \(\pm\)5.0 mm/year. The study presented by [PERSON] et al. [22] showed that the SBAS technique provides an estimate of the mean deformation velocity with a standard deviation of about 1 mm/year for the ERS SAR dataset. Similarly, [PERSON] et al. [4] found there is strong correlation between the MT-InSAR and leveling measurements and the root mean square error was about 6.1 mm/year, suggesting the reliability of InSAR-derived subsidence rates. At the same time, some studies focused on a comparative analysis of inversion results on land subsidence obtained by different MT-InSAR methods. For example, [PERSON] et al. [23] applied two MT-InSAR approaches on 38 ENVISAT images to map Mexico City subsidence, finding that the subsidence information gained from the SBAS method portrays the local characteristics associated with urban constructions and basic facilities, while the PS method quantitatively characterizes the movement of single objects. [PERSON] et al.