## 4 Results  
### Comparison of Annual Deformation Rate  
During data processing, it was found that the image quality of the Sentinel\(-\)1A data from 28 September 2021, 10 October 2021, and 7 June 2022, was very unsatisfactory. In order to ensure the quality of overall performance, these three images were removed, and the remaining 34 interference pairs were used for subsequent processing. Thus, the deformation data from 22 October 2021, to 2 May 2022 were obtained from Sentinel\(-\)1A. After ALOS/PALSAR\(-\)2 was optimized, the remaining 25 interference pairs are subjected to subsequent processing. One of these images, the image from 4 June 2022, has a large difference from the phase center of the others and was thus eliminated. The final deformation data were obtained from 25 September 2021 to 7 May 2022. The monitoring accuracies of ALOS/PALSAR\(-\)2 and Sentinel\(-\)1A are 26.8 m and 9.65 m, respectively. When a region is deformed, most of the deformation-rate pixels should be unstable, with obvious clustering properties [53; 63]. These are considered to be real deformation regions, and the error is usually expressed as discrete deformation points. Figure 5a,b show the original deformation-rate results obtained by IPTA\(-\)SBAS. Although the atmospheric error, DEM error, and orbital error were removed during data processing, there are still residual and newly introduced error phases. The final result contains some discrete error points, which usually greatly affect the speed and accuracy of subsequent landslide interpretation [63]. The number of discrete error points in the deformation-rate results is also an important indicator of the monitoring quality of SAR data. This experiment uses hotspot-analysis technology to identify obvious cold spots, hotspots, and discrete unstable points in the annual average rate results. The discrete error of Sentinel\(-\)1A accounts for 5% of the total error, and the error point is located in the high-vegetation-coverage area. Reliable detection results from built-up areas were validated with almost no discrete error points (Figure 5c). However, most of the slopes in this area are less than 10\({}^{\circ}\) and are unlikely to experience landslides. The error ratio of ALOS/PALSAR\(-\)2 is 3%; its discrete error points are relatively few and evenly distributed, and the error points are not strongly correlated with terrain changes (Figure 5d). Therefore, the reliability of ALOS/PALSAR\(-\)2 is still higher than that of Sentinel\(-\)1A in terms of the overall deformation rate. After discrete error points are removed, the final average annual deformation rate is obtained. As shown in Figure 6a,b, the effective monitoring areas of ALOS/PALSAR\(-\)2 and Sentinel\(-\)1A are 88.4% and 72.58%, respectively. The superior penetration of ALOS/PALSAR\(-\)2 makes it theoretically better suited to monitoring potential geohazards. The average annual deformation rates of both data types are close to a normal distribution, and the mean values of Sentinel\(-\)1A and ALOS/PALSAR\(-\)2 are \(-\)5.63 mm/year and \(-\)6.26 mm/year, respectively, which indicates that the study area is relatively stable. The difference between the annual average deformation rates of the two is calculated. It is  
Figure 5: Original annual line-of-sight (LOS) deformation-rate results. (**a,b**) represent the annual LOS deformation rates obtained from Sentinel\(-\)1A and ALOS/PALSAR\(-\)2 data, respectively. A positive value (blue) indicates that the deformation direction detected by the satellite is close to the satellite flight direction, while a negative value (red) indicates that the detected direction of deformation is away from the satellite; (**c,d**) are the discrete error points in the Sentinel\(-\)1A and ALOS/PALSAR\(-\)2 velocity diagrams, respectively. found that points with large differences are mostly distributed in areas with relatively lush vegetation (Figure 7c), and the overall distribution still follows a normal distribution, with an average value of \(-3.54\) mm (Figure 7d).