## 3 Methodology
### 3D Modeling Results  
The results obtained from the above process were six 3D point clouds, six textured 3D models, three panorama images, and the corresponding orthomosaics. More specifically, as shown in Table 3, the datasets created from a flight altitude of 60 m had the higher resolution (1.91 cm) and the largest number of points and faces in the dense point cloud and 3D mesh as expected. The GSD for the scenarios realized at 80 m and 100 m flight altitudes were 2.53 and 2.98 cm, respectively. As both had a coarser resolution, the values of points and faces were smaller than those of scenario 1 and 4. As expected, when the flight altitude got higher, the number of points and faces of the dense point cloud and 3D mesh got lower due to the coarser information depicted in the drone images (Figure 7). In addition, three different panoramas were created, one from each flight altitude (60 m, 80 m, 100 m). The first panorama was created from 43 images collected at the 60 m altitude and consisted of 23,073 \(\times\) 11,537 pixels (Figure 8). The second (80 m) and third (100 m) panoramas also consisted of 43 images with the same amount of pixels. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Dataset/Scenario** & **Dense Point Cloud** & **3D Mesh** & **Orthomosaic** \\ \hline \multicolumn{4}{c}{Overlap 80\% and 60\%} \\ \hline Scenario 1 (60 m) & 25,945,545 points & 5,189,002 faces & 1.91 cm \\ \hline Scenario 3 (80 m) & 21,989,749 points & 4,397,949 faces & 2.53 cm \\ \hline Scenario 5 (100 m) & 19,294,674 points & 3,858,934 faces & 2.98 cm \\ \hline \multicolumn{4}{c}{Overlap 90\% and 70\%} \\ \hline Scenario 2 (60 m) & 28,702,725 points & 5,740,520 faces & 1.91 cm \\ \hline Scenario 4 (80 m) & 25,003,619 points & 5,000,723 faces & 2.53 cm \\ \hline Scenario 6 (100 m) & 19,768,631 points & 3,953,726 faces & 2.98 cm \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Number of points in the dense point cloud and mesh faces for each data set. Figure 6: Spherical panoramas generated from images (60 m). Evaluation of 3D Models  
The selection of the 3D model and the panorama for the geovisualization were based on the most detailed and geometrically correct 3D mapping of the geosite. As shown in Figure 9, gaps appeared in the point cloud on the vertical and dark sides in a gorge section with irregular slopes. The point cloud created from the images collected from the 60 m flight with 80% front and 60% side overlap showed significant gaps on its north side. The same was observed in all the point clouds (80 m and 100 m) created from the acquired images with the same overlap (80% and 60%). The significant gaps in the 3D point clouds significantly affected the creation of 3D models as they determined their geometry. The point clouds constructed from the flights' images with 90% front and 70% side overlap showed a greater number of points on the vertical sides at the respective flight altitudes. However, in Figure 9b,f discontinuities were observed in the point cloud, which indicated the absence of information in these specific sections. In the case of Figure 9d, the created point cloud did not show significant gaps and discontinuities in the distribution of points on the steep slopes and represented the geometry of the geosite more precisely. The visual observation made through the quality control mentioned above was confirmed by quantitative means of the cloud-to-cloud (C2C) distance algorithm of cloud comparison [69]. Initially, all (six) 3D point clouds were introduced into the Cloud Compare software (CloudCompare 2.11, 2020) and were segmented to the same extent. The point clouds were then registered on a reference cloud. The point cloud with the highest density was selected as the reference cloud and used to register all the other clouds. Then the C2C  
Figure 8: Panorama of images from a 360\({}^{\circ}\) shot at 80 m.  
Figure 7: 3D model of the Voulgaris gorge, from scenario 4 (80 m altitude and 90% and 70% overlap).