## 4 Results and Discussion
### Ascending Dataset Results  
The image processing was conducted using the CPT-TPC algorithm, which analyses RTs directly identified on the ground, allowing the evaluation of any displacement over time.  
The first step of the processing was the co-registration. The master image was automatically identified by the software, which is capable of selecting it, minimizing total decorrelation in generating all interferograms. As discussed earlier, 97 images acquired in ascending geometry from 6 January 2017 to 12 November 2022 were used, and 352 interferograms were generated (Figure 6), allowing the analysis of individual pixels that show a specific quality/stability in terms of phase.  
Specifically, the acquisition on 8 August 2019 was chosen as the master image for the co-registration of the entire stack of images. After that, the first results obtained from the elaboration are (Figure 7): (a) the Radar Targets Map and (b) the Triangulation Map.  
In particular, the Radar Targets identified map (Figure 7a) shows the points on the ground that generates a consistent radar signal over time. By analyzing the displacement of these Radar Targets, we can obtain accurate information on surface deformations in the study area. The Radar Targets identified image provides a visual representation of the distribution of these targets and their displacement patterns, aiding our interpretation of the landslide dynamics. On the other hand, the Triangulation Map images (Figure 7b) are used to display the interferometric phase measurements for each Radar Target, which are then converted into displacement values. These images help us understand the spatial distribution of the measured displacements and identify areas with significant deformation. By comparing the Triangulation Map images obtained from ascending and descending geometries, we can also gain insights into the different displacement components, such as vertical and horizontal movements. At the end of the processing, both the mean displacement rate map along the LoS of the RTs (Figure 8) and the time series were provided. It should be emphasized that the latter represents cumulative displacements from the first available image, while the mean displacement rates represent a sort of linear velocity that the model estimates over the entire acquisition interval. As can be seen, a high number of RTs (about 53,188) were identified in the investigated area, resulting from the outstanding electromagnetic response of existing structures. In contrast, heavily vegetated environments are characterized by fewer targets, making them difficult to investigate. In detail, 27,504 RTs were used in ascending geometry to analyze the San Marco dei Cavoti village, with a density of approximately 7457 RT/km\({}^{2}\). These targets present mean displacement rates along the LoS up to 2.5 cm/year, particularly in the western sector of the study area. Overall, the recorded displacement rates refer to slow kinematics, with maximum displacement velocities of a few centimeters per year. As shown in Figure 8, the most interesting area is located close to the San Marco dei Cavoti village, to the southwest. The area shows several substantial amount RTs with high rates.  
Figure 6: Interferogram distribution in ascending geometry in the analyzed time interval.  
Figure 7: (**a**) Radar Targets identified; (**b**) Triangulation Map.