## 3 Results
### Image Analysis  
Scene 1-1 covers the area from Osong Station in Cheongju to Sejong City, which is characterized by extensive mountainous terrain. As a result, the railway in this section predominantly passes through tunnels rather than running on the surface. To effectively extract a high-density point cloud under these conditions, Sparse Point Processing was applied. In total, 15,565 persistent scatterer (PS) points were extracted from this scene by applying an Amplitude Stability Index (ASI) threshold of 0.75 or higher to ensure data reliability. The extracted points were connected through 155,853 linkages using the Local Redundant method, which enhances the robustness of the network by creating multiple redundant connections between neighboring points. Since this section represents the starting point of the Honam High-Speed Railway, the track alignment follows a curved path rather than a straight line. Consequently, the connection range parameter for point linking was set lower than in other regions to account for the geometry of the railway. The final deformation pattern of Test Area 1-1 is shown in Figure 5.  
The area covered by Scene 1-2 is located to the right of the mountainous region and extends from Buyeo City to Nonsan City in Chungnam Province. Unlike the previous section, this area contains very few mountainous regions. However, it is largely composed of agricultural land rather than urban areas with high radar reflectivity, resulting in a relatively low number of high-density persistent scatterers (PSs). To compensate for this, a combined index of the Amplitude Stability Index (ASI) and Spatial Coherence was applied, selecting points where the ASI + Spatial Coherence > 1.5 to ensure the reliability of the extracted PS points. After applying Sparse Point Processing, a total of 8290 PS points were extracted from this section. The total number of connections established between the points was 82,900 using the same Local Redundant method as in Scene 1-1 to maintain network stability through overlapping connections. The final deformation pattern of Test Area 1-2 is shown in Figure 6.  
Figure 5: Final ground deformation map for Test Area 1-1. In this study, the analysis was conducted by subdividing the area into two separate scenes, as described above. For each scene, persistent scatterers (PSs) were extracted using selection criteria and connection methods tailored to the specific topographic characteristics of the region. These extracted PS points were then processed through phase unwrapping, allowing them to be converted into single-value pixels within the ground deformation map. The extracted point clouds were ultimately used to calculate ground deformation along the Honam High-Speed Railway (KTX) and its surrounding areas, which is the primary objective of this study. Table 2 summarizes the processing techniques applied to each scene, along with the total number of extracted persistent scatterers and the number of established connections. To calculate the final ground deformation values, a phase unwrapping process was performed. Phase unwrapping is the procedure of converting wrapped phase values, which are constrained within a specific range (typically from \(-\pi\) to \(\pi\)), into continuous, unwrapped phase values. Wrapped phase values are restricted within this fixed range, and the relative differences between adjacent pixels can be obtained by integrating these phase differences. This integration process is referred to as phase unwrapping. In this study, the previously constructed Delaunay triangulation network was used to guide the unwrapping of the wrapped phase values of the persistent scatterers (PSs). Through this method, the constrained phase values were successfully transformed into continuous, meaningful values.