## 4 Results
A similar processing methodology was followed with the Porto Katsiki cliff TLS data, even though it was based on more objective management of the mesh product, due to higher point density and a lack of any kind of vegetation altering the slope morphology, which led to impressive and much more clear results (Figure 8a). A large number of facets (23,380 records) were identified, each one characterized by dip and dip-direction measurements, among other location and precision information, which was extracted following the above-mentioned methodology. Several groups of oriented facets were recognized and classified according to their dip (shown with color coding in Figure 8b). The facets were grouped based on their dip direction in six categories shown with different colors in Figure 8c. Each classification contained classes that were assigned different colors, providing images where sectors with similar rock mass characteristics regarding the discontinuity orientation were defined (Figure 8d). At the next stage, the prone area was segmented into each one of those sectors, which seem to behave homogenously in the context of safety due to rockfalls. The average slope orientation characteristics were calculated using tools provided by CloudCompare freeware [98], and the facet list was filtered by excluding the morphology facets and keeping the facets that coincide with rock fracture discontinuities (6175 records). The latter was used at the next step of the kinematic analysis related to the wedge-sliding risk along the prone. Specifically, at the northern morphological segment (Blue plane at Figure 8d) where the plane of the average slope is calculated at 81/244, no more than 21.5% of the discontinuity plane combinations would lead to wedge sliding (Figure 9), which is the most common in this prone area, considering that the limestone friction angle is set at 30\({}^{\circ}\). The percentage rises to 27% for the median segment (Green plane at Figure 8d), where the average slope is oriented at 68/287 and almost reaches 32% for the southern segment (Red plane at Figure 8d). Therefore, it is apparent that the factor of safety in the context of visiting this beach is rather critical, but it is significantly increased while moving to the southernmost segments of the beachfront. Additionally, a back analysis indicates that the rock mass sensitivity to failure increases at the intersection of the three segments since several fallen blocks are found adjacent to these locations. Taking into account the results from the UAV and TLS surveys in Egremnoi and Porto Katsiki coastal areas, respectively, as well as the data obtained from the statistical analysis of the slope discontinuities, we can draw important conclusions about the condition of the slopes and their response to a possible strong earthquake in the future. As emerged from the statistical analysis of the discontinuities and the kinematic analysis of the wedge-sliding risk for the Egremnoi slope, the percentages of facet pairings, which are under serious rockfall potential in the case of an earthquake occurrence, vary from 23 to 29%. Based on this small difference from section to section of the slope, as well as its overall response during the Lefkada earthquake in November 2015, as shown in Figure 3b,c, it is concluded that the slope is characterized by a uniformity in the discontinuities' orientation and its response to strong shocks. Figure 8: The geometrically corrected point cloud of the Porto Katsiki cliff, above the beach, in real color (**a**). The generated mesh file was classified according to each facet’s dip in degrees (**b**) and each one’s dip direction (**c**). The latter led to (**d**) a cliff segmentation into three generic morphological planes; Blue (81/244), Green (68/287) and Red (63/301). However, nothing similar emerges for the coastal slope in Porto Katsiki.