## 4 Results and Discussion
### Descending Dataset Results
The A2 time series is interesting as it shows a certain displacement (up to \(-6\) mm) in a zone where no landslide was previously recognized. This could be a sign of the presence of a slope process that could have either (i) not been recognized because of the vegetation or human activities and (ii) an uphill, retrogressive enlargement of the already recognized landslide. Something similar happens with the descending time series: D1 and D4, located on a landslide, show slow movements, most likely related to the landslide. On the other hand, D2, D3, D5, and D6 are located on the slope in zones where there are no recognized landslides. Especially in the case of D5 (up to 14 mm of displacement), these movements are most likely related to landslide activity. D5 and D6 are located uphill of landslides in the San Marco dei Cavoti village's limits. A similar result is obtained from the analysis made with the decomposition of the rates. Combining the Ascending and Descending data, it is possible to decompose the velocity obtained along the LoS of the satellites. It should be noted that only the horizontal (W-E direction) and the vertical decomposition analysis can be performed. This is due to the satellite orbits, which are almost perfectly N-S. Displacements along the same direction of the satellite are not detected, which means that a perfectly N-S-oriented landslide is more challenging to detect than a W-E-oriented one. Given the morphology of the area southwest of San Marco dei Cavoti (Figures 12 and 13), the satellites can detect the landslides within the area in both ascending (landslides along the slope exposed to the SW) and descending (landslides along the slope exposed to the SE) geometries. Since the remaining part of the analysis carried out is based on the kinematic relationships between the W-E components and the vertical components, the lack of the N-S component has a negligible impact on our study. Figure 13: Location of descending time series (D1–D6). Usually, when the original data from the two geometries show a discordant movement (Figures 14 and 15), the predominant component is the horizontal one. On the other hand, when the ascending and descending data show a concordant movement, the main component of the rate is the vertical one. Comparing the ascending and descending geometries allows us to assess the potential failure mechanisms that might be driving the observed surface deformations. By examining the spatial distribution of vertical displacement rates, we can explore whether the data points to specific failure mechanisms, such as roto-translational or planar displacement. For instance, if the spatial distribution of vertical displacement rates reveals greater values at the rear of the unstable area, it could indicate a roto-translational mechanism. Figure 14: (**A1–A6**) Ascending time series. (**D1–D6**) Descending time series. On the other hand, if the rates appear to be spatially homogeneous, it might suggest a planar displacement mechanism. As the resolution of the COSMO-SkyMed data is 3 m, these components are obtained using a 10 m sized grid cell. This way, more data are usually used during the computation. The two components are the horizontal one along the \(x\)-axis (E-W) (Figure 15), which shows a maximum rate of \(-5.7\) cm/year (towards the West) and \(4.9\) cm/year (towards the East), and the vertical one (along the \(z\)-axis, as the N-S direction is the \(y\)-axis) (Figure 16), showing a top rate of \(1.4\) cm/year (uplift) and \(-3.4\) cm/year. The obtained movements comply with the existing data and the geomorphology, as the landslide right next to the village of San Marco dei Cavoti is located on a southwestern slope. This follows the observed horizontal component, which is negative (towards the West). As shown in Figures 8 and 11, most of the movement is located along the slopes in the South and southwest areas of the village, while the rest of San Marco dei Cavoti appears to be stable.