## 4 Analysis of the Rock Mass Discontinuities  
The DSE (Discontinuity Set Extractor, v.2.5) software was used to extract the orientation of rock mass discontinuities based on the rock slope point cloud calculation model in Figure 5b [30]. The calculation method is generally divided into three steps: (a) initial candidate point search for K-nearest neighbor points; (b) coplanarity test and best plane fitting; and (c) determination of the rock discontinuity boundaries. For steps (a) and (b), each point in the point cloud data find their K-nearest neighbor points to create a set through the K-nearest neighbor algorithm, and coplanarity tests on all sets containing k+1 points were performed. The MATLAB function KNN search uses an algorithm that provides a quick and efficient way to find the KNNs using a selected norm [30]. In the  
Figure 4: Distribution of the photo position using the UAV method. Figure 5: The 3D point cloud models of the scanned rock slope using UAV. (**a**) Original point cloud data including noise points and rock debris. (**b**) The treated point cloud model by Cloud Compare software. proposed approach, KNNs are calculated by using the KNN search function and the Euclidean distance. For step (c), the eigenvalues \(\lambda_{1}\), \(\lambda_{2}\), and \(\lambda_{3}\) of each point in the point cloud data were obtained through the PCA algorithm, and the deviation value \(\eta\) of each point was calculated and then compared with the deviation threshold (\(\eta_{\text{max}}=20\%\)) to determine whether the point cloud belongs to the same rock discontinuity. The best plane was fitted when the calculations of all points were completed, and the normal vector of the fitted best plane and the angle (\(\theta\)) with the normal vector of the external point of the structural plane were calculated. The structural plane boundary was then determined by comparing the angle threshold (\(\theta_{\text{max}}=20^{\circ}\)) and the \(\theta\), and whether the external point is included in this rock discontinuity was also determined. The above steps comprise the basic calculation for the point cloud data, which facilitates the next step of obtaining rock discontinuity orientation and performing dominant grouping calculations. The extraction of the rock discontinuity information based on UAV photogrammetry technology based on the above calculation methods is shown in Figure 6.  
Based on the above calculations (Figure 6), the orientation information of rock mass discontinuities can be obtained. Rock mass discontinuities with similar or identical orientations were grouped, and similarity measurements were then performed to determine the dominant orientation groups of the rock slope surface; the calculated results are shown in Figure 7a. In the dominant grouping results of Figure 7a, the same colors represent the same dominant groups of point cloud distributions of exposed rock discontinuities on the slope. Since the studied slope surface exhibits an overall arcuate shape, as illustrated in the plan view of Figures 5 and 7a, in order to more clearly present the dominant grouping of the exposed rock discontinuities on the studied surface, the rock slope surface was further divided into left and right dominant groupings, as shown in Figure 7b,c. Figure 6: The simplified process of extraction for the orientation of rock mass discontinuities. The orientation of rock mass discontinuities can be described by three parameters: strike, dip direction, and dip angle. Usually, since the dip direction and strike can be interconverted, rock mass discontinuities are often characterized by dip direction and dip angle.