## 3 Results
### Accuracy Assessment of DSMs  
The evaluation of the accuracy of the extracted DSMs was executed through the computation of RMSE, which estimates the differences between the values of a DMS and the reference high-precision values. The computation is performed by the following equation:  
\[RMSE=\sqrt{\frac{1}{n}\sum_{i=n}^{n}\left(h_{ref}-h_{i}\right)^{2}} \tag{2}\]  
where \(h_{ref}\) is the reference elevation, h\({}_{i}\) is the DSM elevation at point \(i\), and \(n\) is the number of GCPs. A basic condition for the performance of the calculation is that the reference data should be an order better than the data to be evaluated. Thus, GCPs with sub-millimeter accuracy were utilized as reference points in the current study.  
The variations in the elevation values between the reference data and the respective photogrammetric DSMs, acquired by different viewing geometries over all case studies, are presented in Table 6. It is obvious that the synergistic use of nadir- and oblique- viewing images during UAV campaigns managed to minimize the elevation errors in most DSMs.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Case Study ID**} & **Acquisition** & **Near Distance (m)** & **Near Distance (m)** \\  & **Geometry** & **Mean Center of Line 1** & **Mean Center of Line 2** \\ \hline \multirow{3}{*}{Moira} & Nadir & 0.023 & 0.095 \\  & Oblique & 0.015 & 0.049 \\  & Synergistic use & 0.013 & 0.012 \\ \hline \multirow{3}{*}{Egkremni} & Nadir & 0.020 & 0.022 \\  & Oblique & 0.025 & 0.014 \\  & Synergistic use & 0.038 & 0.021 \\ \hline \multirow{3}{*}{Zachlorou} & Nadir & 0.006 & 0.016 \\  & Oblique & 0.070 & 0.068 \\  & Synergistic use & 0.023 & 0.010 \\ \hline \multirow{3}{*}{Messarista} & Nadir & 0.064 & 0.036 \\  & Oblique & 0.477 & 0.305 \\  & Synergistic use & 0.082 & 0.034 \\ \hline \multirow{3}{*}{Patras Port} & Nadir & 0.700 & 0.812 \\  & Oblique & 0.946 & 0.890 \\ \cline{1-1}  & Synergistic use & 0.024 & 0.009 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Near distances of mean centers resulting from the reference mean centers of geodetic lines 1 and 2.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{
\begin{tabular}{c} **Case Study** \\ **ID** \\ \end{tabular} } & **Acquisition** & **Length** & **Difference** & **Difference** & **Area (m2)** & **Difference** & **Difference** \\  & **Geometry** & **(m)** & **(m)** & **\%** & **(m2)** & **(m2)** & **\%** \\ \hline \multicolumn{5}{c}{Reference} & 0.538 & 0.150 \\ \hline \multirow{3}{*}{Zachlorou} & Nadir & 0.546 & \(-\)0.008 & \(-\)1.486\% & 0.149 & 0.001 & 0.666\% \\  & Oblique & 0.548 & \(-\)0.010 & \(-\)1.858\% & 0.148 & 0.002 & 1.332\% \\ \cline{1-1}  & Synergistic use & 0.542 & \(-\)0.004 & \(-\)0.743\% & 0.151 & \(-\)0.001 & \(-\)0.666\% \\ \hline \hline \end{tabular}
\end{table}
Table 5: Comparison of the dimensions of the aluminum target between the different acquisition geometries.  
In particular, the RMSE for the DSM arising from the combined use of nadir and oblique imagery in the case study of Egnemni, was calculated at 0.083 m, while the respective errors for the nadir-viewing and oblique-viewing DSMs were estimated at 0.092 m and 0.085 m, respectively. Furthermore, in the case study of [PERSON], the RMSE for the DSM that emerged from the simultaneous processing of nadir and oblique imagery was calculated at 0.090 m. The respective RMSE for the nadir-viewing DSM was computed at 0.162 m, while the error of the oblique-viewing DSM was notably larger (i.e., 0.357 m).  
Although oblique-viewing images demonstrated an overall good performance in the generation of DSMs, we noticed a correlation between the UAV acquisition geometry and the topographic characteristics of the survey area. Specifically, nadir-viewing geometry was considered more suitable for DSM generation in flat urban (case study 5) or densely built-up (case study 4) areas, since it revealed smaller values in elevation variations than oblique imagery.