## 3 Results
### Data Integration and Cross-Validation
The accuracy (mean error) of the position of MLS and MSLS points relative to the DGNSS matrix is within 0.08-0.09 m relative to the matrix, which was measured with a mean error of 0.03 m. This result is within the measurement accuracy of both systems, confirming the validity of the measurements taken. The accuracy of the MLS measurements was also verified on the Brodowski Bridge (study area b), where tachymetric measurements were made to the targets (Figure 12). Lengths were compared between homologous points measured with Total Station and the point cloud developed with MLS. The mean error of the MLS relative to the Total Station measurements (vector length error) was determined as m\({}_{0}\) = 0.025 m, which was defined as a satisfactory result. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \multicolumn{5}{c}{**Mean Errors of Control Points**} \\ \hline  & **MLS [m]** & & & **MSLS [m]** & \\
**X** & **Y** & **Z** & **X** & **Y** & **Z** \\ \hline
0.034 & 0.048 & 0.059 & 0.046 & 0.044 & 0.056 \\  & & \multicolumn{5}{c}{**Accuracy of point**} \\  & \(m_{0}=8.35\times 10^{-2}\) & & \(m_{0}=8.53\times 10^{-2}\) & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Accuracy of MLS and MSLS. \begin{table}
\begin{tabular}{c c c} \hline \hline
**GSD [m]** & \multicolumn{2}{c}{**Mean Errors [m]**} \\ \cline{2-3}  & **GCP** & **ICP** \\ \hline \(3\times 10^{-2}\) & \(2.1\times 10^{-2}\) & \(3.5\times 10^{-2}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Accuracy estimation of control points. Aerial data via ALS and ALB were integrated into an aerial platform (aircraft) that was used to plan a synchronous mission. After the integration of the data, based on algorithm (5), the accuracy of their fit was checked. This was realised in two ways, through cross-sectional analysis and error analysis of adjustment points. Examples of point cloud integration are shown in Figures 13 and 14. Figure 12: MLS validation measurements against Total Station (study area Brodowski Bridge). (**a**) real view, (**b**) reference points located on the bridge, (**c**) reference points located outside of the bridge. Figure 13: Examples of integration of ALB and MLS point clouds. The achieved accuracies of temporal-spatial integration of point clouds are shown in Table 7.  
Figure 15 shows the validation of ALB measurements against geodetic measurements on water and land. The achieved accuracies show conformity to a normal distribution with a standard deviation of 0.1 m. The top graphs (Figure 15) show the magnitudes of uncertainty in the (from left) XY, XZ, and YZ planes. In each of the cases shown, a random distribution of errors can be seen both in magnitude and position. The histograms of the uncertainties in the X and Y coordinates are further illustrated in the bottom row of the graphs. These histograms show that the distribution of errors is normal. In fact, the data in both cases (for water and land) are similar and within a mean error of about 0.07 m. At the same time, a comparison of the height of the point cloud against classical hydrographic measurements (Figure 15f) shows that the differences are even smaller, as the average error does not exceed the value of 0.05 m. \begin{table}
\begin{tabular}{c c c c c c} \hline  & \multicolumn{4}{c}{**Mean Errors [m]**} \\  & \multicolumn{4}{c}{**Similarity Transformation (Traditional Approach)**} \\
**X** & **Y** & **Z** & **X** & **Y** & **Z** \\ \hline
0.084 & 0.092 & 0.123 & 0.113 & 0.213 & 0.301 \\  & \multicolumn{4}{c}{**Accuracy of point**} \\  & \multicolumn{4}{c}{\(m_{0}=1.33\times 10^{-2}\)} & \(m_{0}=1.94\times 10^{-2}\) \\ \hline \end{tabular}
\end{table} 
Table 7: Accuracy of time and spatial data integration. Figure 14: Examples of integration of ALS, ALB, MLS, MSLS, and MBES point clouds of Brdowski Bridge.