## 4 Results  
This analysis assumes the diagnostic train levelling measurement data as a reference, disregarding any potential flaws that might impact the data. Based on the European Norm [66], the stability of a rail segment for high-speed trains traveling at speeds of 220-300 km/h is determined. According to these criteria, a rail segment is considered stable if it maintains a structurally healthy condition with a settlement of less than 6 mm. Conversely, a rail segment is deemed potentially unstable if it has a settlement greater than 6 mm [5,66]. By comparing the results of the PS-InSAR analyses of the 30 km railway line and the diagnostic train measurements in areas 1 and 2, it is evident that areas 1 and 3 are not stable, whereas area 2 remains stable based on the cumulative results of the two-year time series graphs (Figure 11).  
The correlation was assessed using the Pearson Product Moment Correlation Coefficient, and the determination of correlation relations between each dataset relies on the overlapping zones generated by the PSs in the profiles of the first and second research regions. The correlation coefficients for study area-1 between the diagnostic train and CSK analysis is 0.78, with S1-B/T65 at 0.93, and lastly with S1-B/T160 at 0.69. Hence, there exists a robust and favorable association between the datasets. For study area 2, the correlation coefficient between the diagnostic train and the CSK analysis is 0.88, with S1-B/T65 at 0.65, and lastly with S1-B/T160 at 0.87. Therefore, there is a strong and positive correlation between the datasets for the second study area (Table 5).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **\# of PSs on the** & **Mean** & **Mean Std.** \\  & **Railway Line** & **Coherence** & **Dev. (mm/yr.)** \\ \hline \multicolumn{4}{c}{Study Area-1} \\ \hline CSK & 83 & 0.67 & 2.32 \\ S1B/T65 & 57 & 0.79 & 3.04 \\ S1B/T160 & 47 & 0.84 & 2.62 \\ \hline Study Area-2 & & & \\ \hline CSK & 127 & 0.92 & 0.98 \\ S1B/T65 & 82 & 0.87 & 2.37 \\ S1B/T160 & 86 & 0.90 & 1.92 \\ \hline Study Area-3 & & & \\ \hline CSK & 4 & 0.78 & 1.75 \\ S1B/T65 & 4 & 0.81 & 3.08 \\ S1B/T160 & 4 & 0.76 & 3.34 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Attributes of the PSs located on the railway lines in research areas 1, 2 and 3.  
Since there is no measurement from the train for the third study area, the correlation coefficients were calculated only between the clustered PSs. This information is shown in Figure 12 and Table 6. For this correlation analysis based only on InSAR outputs, due to differences in measurement time, values one month apart are used as a basis by calculating the average deformation for the relevant PS. These PSs are specially chosen from railways that run through the station and are also utilized as parking lots. As seen in Table 6, there is a significant and robust positive correlation between these PSs obtained from different SAR datasets.  
Figure 11: Vertical accumulated subsidence profiles of the railway along the 1 st and 2 nd study areas: (a) CSK; (b) S1–B/T65; (c) S1–B/T160; and (d) diagnostic train measurement time-series graphs.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{3}{c}{**Study Area-1**} \\ \hline  & S1B/T65 & S1B/T160 & Diagnostic Train \\ \hline CSK & 0.748 & 0.870 & 0.780 \\ S1B/T65 & & 0.699 & 0.930 \\ S1B/T160 & & 0.690 & 0.690 \\ \hline \multicolumn{3}{c}{**Study Area-2**} \\ \hline  & S1B/T65 & S1B/T160 & Diagnostic Train \\ \hline CSK & 0.634 & 0.914 & 0.880 \\ S1B/T65 & & 0.635 & 0.650 \\ S1B/T160 & & & 0.870 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Comparison of correlation coefficients of diagnostic train and InSAR measurements for 1 st and 2 nd areas.