## 3 Research Methods  
### PS-InSAR  
The technical approach known as PS-InSAR was introduced by [PERSON] et al. [19] and detects highly correlated and stable points, namely permanent scatterers. Based on the amplitude and phase data of images, it can define ground objects such as buildings, artificial structures, rocks, and ridges. This possesses the capability of sustaining prolonged temporal sequences with elevated coherence and robust scattering. The algorithm in question is outlined as follows. It acquires N + 1 SAR images encompassing the identical region, which could designate a single image as the reference image. It also carries out registration, resampling, de-flattening, and topographic phase and interference processing to obtain N-interference images. The diagram in Figure 2 illustrates the space-time baseline. The reference DEM and satellite orbit data are used to perform topographic correction on the interferogram. The phase of the interferogram \(\phi_{x,i}\) at the \(x\) position of the \(i\) interferometer pair can be expressed as Equation (1). \[\phi_{x,i}=\phi_{def_{0},x,i}+\phi_{top_{0},x,i}+\phi_{const,x,i}+\phi_{slope,x,i}+\phi_{atm,x,i}+\phi_{noise,x,i} \tag{1}\]  
The sum of the three components \(\phi_{const,x,i}\), \(\phi_{slope,x,i}\), and \(\phi_{atm,x,i}\) is known as the Atmospheric Phase Screen (APS), which represents the constant phase values, the linear phase values due to atmospheric effects, and the nonlinear atmospheric effects, respectively. \(\phi_{def_{0},x,i}\) and \(\phi_{top_{0},x,i}\) denote the surface deformation phase in the radar line-of-sight direction and the terrain phase due to DEM errors, respectively. \(\phi_{noise,x,i}\) denotes the noise phase (errors introduced by scatterer variations, thermal noise, alignment errors, etc. ). \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Band (wavelength in cm) & C (5.6 cm) \\ Imaging mode & Sentinel-1A IW \\ Incident angle & 44.01 \\ Polarization mode & VV \\ Spatial resolution & \(5\times 50\) \\ Revisit period/d & 12 \\ Number of images & 41 \\ Pass direction & Ascending \\ Time span & From 11 January 2020 to 27 October 2022 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Fundamental parameters of SAR images. On 8 October 2021, the super master image was chosen. Initially, a linear model is employed to estimate the residual height correction coefficient and average deformation rate of the potential PS points before an initial inversion. In this process, the region is divided into subregions of 2 m\({}^{2}\) in size, and the selection of reference points is based on the index of amplitude deviation. Each subregion is processed individually, and the results from all subregions are then combined to form a complete result. In the case of the second inversion, a linear model of first order is employed for estimating the phase component caused by atmospheric interference. In order to isolate the nonlinear deformation phase \(\phi_{ddv,x,i}\) in Equation (1), one of the key issues is the need to determine the atmospheric phase \(\phi_{atm,x,i}\). In the residual phase, the atmospheric phase and the nonlinear deformation phase have different frequency characteristics in the spatial domains. This is because the atmospheric correlation length in space is about 1 km, which exhibits a high degree of correlation in the spatial domain, i.e., a low-frequency characteristic. However, for an image element, the atmospheric condition can be regarded as a stochastic process at different radar image acquisition times, and the atmospheric phase is a white noise in time, highly uncorrelated in the time domain, i.e., a high-frequency characteristic. In contrast, the nonlinear deformation has a small correlation length in space and a low-frequency characteristic in the time domain. Therefore, we consider separating the atmospheric phases \(\phi_{atm,x,i}\) by obtaining them through temporal high-pass filtering (365 days) and spatial low-pass filtering (1.2 km).