## 4 Case Studies
### Santa Caterina
Actually, when vegetation is present, the photogrammetry by drone is not able to identify the underlying surfaces, differently than the laser scanner equipped with last and first impulse technology, that are capable to partly filtrate the vegetation. The 3D geometrical model obtained through the combined laser scanner-drone survey produced a high-definition point cloud consisting of 55.6 million points (corresponding to a point density of 6950 pt/m\({}^{2}\)), 15.5 million (2000 pt/m\({}^{2}\)) out of which were from the laser scanner, and 40.1 million (3160 pt/m\({}^{2}\)) from the drone (Figure 6). This cloud, properly georeferenced with GPS and Total Station, allowed to measure the bedding and spacing of any plane in the rock mass, which is a crucial element for the following phase of designing the stabilization works. Figure 6: Texturized point cloud at the Santa Caterina cliff. The yellow vertical line provides the height of the cliff. The acquired point cloud underwent first a manual procedure of decimation and filtering to eliminate the spurious elements (vegetation, electric cables, trellis, etc.). The cleaned point cloud was then object of a second step of decimation, according to a grid defined in a way to maintain the sections representative of the rock mass. Then, the geo-structural analysis started on the point cloud by individuating portions of space with similar orientation, to extrapolate the value of attitude in terms of dip/dip direction by applying the algorithm RANSAC (Figure 7). The so identified planes were portrayed on stereonets, and at least five discontinuity sets were detected, summarized in Table 1 and shown in Figure 7.  
Figure 7: RGB point cloud at Santa Caterina rock cliff. Above: mapping the dip direction value attributed to the point cloud over the study area. Below: representation of the dip directions for each individual discontinuity set, distinguished by different colors; in the inset, the steroid shows distribution of the sets. To verify the reliability of the attitudes acquired semi-automatically on the point cloud, some discontinuities in the tuff rock mass were checked on site. In detail, the main discontinuity sets were identified, and traditional measure stations were casually performed by means of the Clar compass. Average attitudes of the main measured discontinuity systems thus obtained are reported in Table 2.  
The above described procedure allowed to compare the structural data obtained with the two different survey techniques [8], which is the traditional, manual, geomechanical survey, and the geo-structural survey from point cloud acquired with TLS and UAV techniques (Figure 8). Comparing the datasets, it appears that the results obtained from geo-structural survey from point cloud fit well those acquired directly on the rock face. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Set** & **Dip Direction** & **Dip** \\ \hline K1 & 15 & 77 \\ K2 & 308 & 76 \\ K3 & 72 & 77 \\ K4 & 165 & 75 \\ K5 & 110 & 75 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Average attitude of the discontinuity sets at Santa Caterina rock cliff, identified through geo-structural analysis on point cloud. Figure 8: Stereoplot comparing the data from the two different techniques. Since the joints show mostly high dipping, variations in the discontinuity polarity are related to the often undulated pattern, which results in opposite sectors within the stereoplot (sets K2 and K4 in Figure 8). As concerns the K5 set, this was only identified through geo-structural analysis on point cloud. This is because such system is rarely shown in the rock mass, practically consisting of very few joints with high spacing; therefore, the direct acquisitions in correspondence of a limited sector of the rock face, accessible on the ground, did not allow to point out its presence.