## 3 Data Results and Analysis
### Comparison Analysis of PS-InSAR Results and Second Order Leveling Data  
To verify the reliability of PS-InSAR technology in monitoring the slope deformation of the high-fill canal of the South-North Water Diversion Project, eight benchmarks in the study area shown in Figure 6a were selected for comparison and verification. The deformation of the PS point line of sight direction is projected onto the vertical direction according to Equation (7), and the second-order leveling data is zeroed out according to the time period. The PS-InSAR monitoring results and the time series displacement changes of the second-order leveling measurement results are shown in Figure 7. The deformation trends match perfectly, which fully proves the reliability of the PS-InSAR technique.  
To further quantify the reliability of InSAR deformation monitoring results, Root Mean Square Error (_RMSE_) was used to evaluate the degree of agreement between InSAR results and level measurement results.  
Figure 7: Variation of PS-InSAR monitoring results from second-order leveling measurements.  
\[RMSE=\sqrt{\sum_{i=1}^{n}\Delta h_{i}^{2}/n}, \tag{8}\]  
where \(\Delta h_{i}\) is the difference between the \(i\)th level data and the resultant settlement of InSAR monitoring data, and \(n\) is the number of selected points.  
The comparison deformation results between the benchmarks and PS points are shown in Table 2. More than 87% of RMSE values are less than \(\pm\)2 mm, the maximum is 3.02 mm; the maximum value of the difference between the two is 6.59 mm. From Figure 7, it can be seen that the time that causes the large fluctuation of the P1 point appears between December 2016 and March 2017, which is mainly caused by the inconsistent matching position of the PS point and benchmark. Meanwhile, it can be found that the P1 point is located at the filling and cutting boundary of high-fill canal, as shown in Figure 3c. In the process of engineering construction, the boundary construction is poor and easy to deform. Moreover, there are three problems in the stability of high fill. First, because the soil subgrade slope of high fill is of high height and poor stability, it is easy to landslide. Second, because the high filling height is larger, it will lead to a large settlement of the foundation under the subgrade, which is easy to damage. Third, due to the high fill soil material problem, in the case of rainfall, infiltration will occur, causing instability to occur easily. Through the above three questions, combined with the position of P1, we believe that this is the reason for the difference between the analyzed values of P1 and other positions. In addition, P1 and P8 also showed strong inconsistency around May 2017. It can be seen from Figure 6 that P1 and P8 were both located in areas with serious canal subsidence. During PS-InSAR processing, the image data cycle was 12 days, which would lead to errors in monitoring values due to time incoherence. The correlation between the PS-InSAR results and the eight benchmarks results is further counted. As shown in Figure 8, the correlation coefficient reaches 0.96, and the RMSE of the difference is 1.279 mm, which is highly consistent with each other in terms of deformation trends and magnitudes. Therefore, it is sufficient to prove the reliability of the PS-InSAR results in this paper.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Point** & **RMSE/mm** & **Mean/mm** & **Maximum Difference/mm** \\ \hline P1 & 3.02 & 2.37 & 6.59 \\ P2 & 0.73 & 0.61 & 1.53 \\ P3 & 1.36 & 1.15 & 2.61 \\ P4 & 1.57 & 1.17 & 4.41 \\ P5 & 1.65 & 1.18 & 4.68 \\ P6 & 1.31 & 0.94 & 3.55 \\ P7 & 1.73 & 1.32 & 4.11 \\ P8 & 1.3 & 1.01 & 3.06 \\ \hline \end{tabular}
\end{table}
Table 2: Comparison of level results with PS-InSAR results.  
Figure 8: Regression analysis of level monitoring and InSAR monitoring formal variables.