## 3 Methodology
### Methodological Procedure  
SBAS-InSAR is an innovative method of time-series analysis, introduced by [PERSON] et al. for the study of low-resolution and massive deformation [36]. The method utilizes short spatiotemporal baselines to generate time-series interferograms from multiple master images through flexible combinations. It employs singular value decomposition (SVD) for matrix inversion to derive the deformation sequences and average deformation rates of the study area over the observation period [37; 38; 39]. Regarding SBAS-InSAR processing, SVD is used to decompose the design matrix into components, allowing for the identification of significant singular values that contribute to the stable solution, while discarding small singular values that correspond to noise or redundant information. This helps in regularizing the inversion process and ensures that the deformation signal is effectively extracted. The application of the SBAS-InSAR technique includes the following steps, as illustrated in Figure 3 [40; 41; 42]. 1. \(N+1\) SAR images of the same region arranged chronologically were obtained. One image was selected as the reference for alignment. The remaining SAR imagery were aligned to the reference image by setting suitable temporal and spatial baseline thresholds, and we generated up to \(\frac{N(N+1)}{2}\) interferometric pairs of the \(N+1\) SAR images. 2. The combined image pairs were subjected to differential interferometry to generate time-series interferograms of multiple primary images. The interferometric phase composition is described as follows: \[\Delta\phi_{i}(x,y)=\Delta\phi_{disp}+\Delta\phi_{topo}+\Delta\phi_{atm}+ \Delta\phi_{res}\] (1) where \(\Delta\phi_{disp}\) denotes the deformation phase (along the radar line-of-sight direction), \(\Delta\phi_{topo}\) denotes the topographic phase, \(\Delta\phi_{topo}\) denotes the air phase, and \(\Delta\phi_{atm}\) denotes the disturbance phase. \(\Delta\phi_{disp}\) and \(\Delta\phi_{topo}\) can be expressed as follows: \[\Delta\phi_{disp}=\frac{4\pi}{\lambda}[d_{t_{1}}(x,y)-d_{t_{1}}(x,y)]\Delta \phi_{disp}=\frac{4\pi}{\lambda}[d_{t_{2}}(x,y)-d_{t_{1}}(x,y)]\] (2)  
Figure 2: Time-position map of Sentinel-1A (**a**) ascending and (**b**) descending data. \[\Delta\varphi_{topo}=\frac{4\pi}{\lambda}\frac{B_{\perp,i}}{r\sin\theta}\Delta Z(x,y) \tag{3}\]  
where \(\lambda\) and \(\theta\) are the wavelength and angles of incidence, \(d_{t_{2}}(x,y)\) and \(d_{t_{1}}(x,y)\) are the accumulated deformations (relative to the reference time \(t_{0}\)) from \(t_{1}\) to \(t_{2}\) along the radar line-of-sight (LOS) direction, and \(\Delta Z(x,y)\) is the terrain error. The terrain phase was corrected using an externally referenced digital elevation model (DEM), while noise was effectively reduced through multi-looking processing and filtering. To calculate the accumulative deformation in the radar line-of-sight (LOS) direction, phase unwrapping was conducted using the minimum cost flow (MCF) method. 1. Ground control points (GCPs) were selected for orbital refinement and re-deplatforming to correct the orbital parameters, and to estimate and remove residual phases and phase changes. 2. Based on a linear model, the residual elevation and deformation rates were estimated first. Unwrapped phases underwent secondary unwrapping, followed by spatial high-pass filtering and temporal low-pass filtering to remove atmospheric phases. This process inversely deduces the temporal deformation sequences and average deformation rates. Finally, geographic encoding was performed to obtain the temporal deformation sequences and average deformation rates in geographic coordinates. This method boasts a high level of precision in surface deformation monitoring, achieving accuracy to the level of centimeters or even millimeters. This capability is vital in promptly detecting subtle deformation indicative of landslides. Furthermore, SBAS-InSAR excels in terms of its extensive coverage, enabling the efficient monitoring of landslide hazards across wide areas.