## 4 Results and Discussion  
This study tested the positional accuracy of geospatial products created from UAV imagery processed with and without GCPs and examined the effects of camera orientation and flight direction. The positional accuracy results for the eleven cases are shown in Table 3. The results showed that the horizontal and vertical accuracies of the geospatial data mainly depended on the quality of the GNSS and IMU on board the UAV, and whether or not GCPs were used in the photogrammetric processing [16]. Overall, the achieved horizontal accuracy was better than the vertical accuracy in all cases. The RMSEs resulting from direct georeferencing based on the consumer-grade GNSS and IMU showed that the accuracy was severely degraded with an H-RMSE and \(Z\)-RMSE of more than 1 and 2 m, respectively. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Processing Steps** & **Parameters** & **Chosen Value** \\ \hline \multirow{2}{*}{Align Photos} & Accuracy & High \\ \cline{2-3}  & Key point limit & 40,000 \\ \cline{2-3}  & Tie point limit & 4000 \\ \hline \multirow{2}{*}{Optimization} & \multicolumn{2}{c}{Fit all constants (f, cx, cy, k1–k4, p1, p2, b1, and b2)} \\ \cline{2-3}  & Quality & Medium \\ \cline{2-3}  & Depth filtering & Moderate \\ \hline \multirow{4}{*}{Build Mesh} & Source data & Dense cloud \\ \cline{2-3}  & Surface type & Height field \\ \cline{2-3}  & Face count & High \\ \cline{2-3}  & Interpolation & Enabled \\ \cline{2-3}  & Point classes & All \\ \hline \multirow{4}{*}{Build Texture} & Texture type & Diffuse map \\ \cline{2-3}  & Source data & Images \\ \cline{2-3}  & Mapping mode & Adaptive orthophoto \\ \cline{2-3}  & Blending mode & Mosaic \\ \cline{2-3}  & Texture size/count: & 4096 \\ \hline \multirow{4}{*}{Build DEM} & Projection & Geographic \\ \cline{2-3}  & Coordinate system & WGS 84/UTM zone 38N \\ \cline{2-3}  & Source data & Dense cloud \\ \cline{2-3}  & Interpolation & Enabled \\ \cline{2-3}  & Point classes & All \\ \cline{2-3}  & Resolution & 0.0532556 m \\ \hline \multirow{4}{*}{Build Orthomosaic} & Projection & Geographic \\ \cline{2-3}  & Coordinate system & WGS 84/UTM zone 38N \\ \cline{2-3}  & Surface & Mesh \\ \cline{2-3}  & Blending mode & Mosaic \\ \cline{2-3}  & Pixel size & 0.013 m \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Setting parameters of Agisoft Metashape used in this study. From the results of the positional accuracy test, reproduced in Table 3, it is clear that the discrepancy was either on the horizontal or vertical planes. From these results, the effect of flight direction and camera orientation on the level of this accuracy was also evident. It can be seen that the best positional accuracy was obtained in the eleventh case (3 cm), in which the DOUBLE GRID MISSION option of the Pix4 Dcapture software was selected to create the flight plan [17]. In this case, the images were acquired with an acquisition angle of 70\({}^{\circ}\), regardless of whether the flight direction was longitudinal or transversal. Figure 7 shows the plots of X, Y, Z, and the total RMSE values for all eleven cases (from the first to eleventh cases). This figure shows the significant difference in RMSEs between the first and other cases, since the first case was based on direct georeferencing, although the onboard GNSS and IMU were of low quality [18]. For further explanation, Figure 8 shows the values of X, Y, Z, and the total RMSEs for the last ten cases (from the second to eleventh cases). Figures 7 and 8 show that the most influential part of the RMSEs in positional accuracy concerned heights (Z-RMSEs) [19]. From the study of all cases, it can be seen that the Z-RMSEs were strongly influenced by the image acquisition angle and flight direction, especially when the checkpoints (CPs) were at a high elevation while the ground control points (GCPs) were at ground level. In this study, the GCPs used for georeferencing, numbered 2, 7, 12, 15, and 18, were at ground level, and all checkpoints except numbers 4 and 11 were also at ground level.