## 3 Data Acquisition and Processing
### Multi-Source Point Cloud Fusion
This completes the rough fusion of multi-source point clouds, but the deviation between different point clouds is large. Therefore, an improved ICP algorithm was used for accurate fusion to complete the multi-source point cloud fusion. The improved ICP algorithm is based on the original ICP algorithm by adding rotation angle constraints and dynamic iteration coefficients [19]; the algorithm flow is as follows. 1. Set the initial value of rigid body transformation \(q_{0}=\left[R_{0},t_{0}\right]^{\mathrm{T}}\), where \(R_{0}\) is the initial rotation matrix and \(t_{0}\) is the initial translation vector;
2. Let \(P_{s0}=R_{0}P_{s}+t_{0}\) and the dynamic iteration coefficient \(h=0\);
3. Estimate the rotation angle boundary \(\theta_{x}\in\left[\theta_{xb}-\triangle\theta_{x},\theta_{xb}+\triangle\theta _{x}\right]\), \(\theta_{y}\in\left[\theta_{yb}-\triangle\theta_{y},\theta_{gb}+\triangle\theta _{y}\right]\), \(\theta_{z}\in\left[\theta_{zb}-\triangle\theta_{z},\theta_{zb}+\triangle\theta _{z}\right]\), where \(\theta_{xb},\theta_{gb},\theta_{zb}\) is the mean value of the rotation angle and \(\triangle\theta_{x},\triangle\theta_{y},\triangle\theta_{z}\) is the deviation value of the rotation angle;
4. Calculate the rotation matrix \(R_{k+1}\) and the translation vector matrix \(t_{k+1}\), and calculate \(q_{k+1}=\left[R_{k+1},t_{k+1}\right]^{\mathrm{T}}\);
5. Calculate the amount of change in two adjacent iterations \(\triangle q_{k+1}\);
6. Calculate \(P_{sk+1}\) to obtain a new rigid body transformation matrix \(\left(R_{k+1},t_{k+1}\right)\); \[\left(R_{k},t_{k}\right)=\underset{R_{k}^{T}R_{k}=t_{n},\text{det}(R)=1,t_{k} }{\text{argmin}}(\sum_{k}\|R_{k}P_{s}+t_{k}-P_{T}\|_{2}^{2})\] (4)
7. Root-mean-square-error judgment: if \(RMS_{k+1}-RMS_{k}>\varepsilon\), then \(h=h+1\); if \(|RMS_{k+1}-RMS_{k}|<\varepsilon\) or \(k>n\), then the algorithm terminates and the iteration ends, where \(\varepsilon\) is the set threshold and \(n\) is the number of iterations. \[RMS=\sqrt{\sum_{i=1}^{N_{S}}\bigl{\|}R_{k+1}Ps_{k+1}+t_{k+1}-P_{T_{k+1}}\bigr{\|} _{2}^{2}}\] (5)  
Through the unified coordinate system and the improved ICP algorithm, the hollow part in the 3D laser point cloud was supplemented by the UAV photogrammetry point cloud, and the fusion of the UAV photogrammetry point cloud and the 3D laser point cloud data was realized. Consequently, we obtained the complete point cloud of the high and steep cliff. At this point, the point cloud data did not have problems such as stratification \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Point**} & \multicolumn{3}{c}{**GPS Measured Coordinates**} & \multicolumn{3}{c}{**Point Cloud Coordinates**} & \multirow{2}{*}{**Error**} \\ \cline{2-2} \cline{4-7}  & \(X\)**/m** & \(Y\)**/m** & \(Z\)**/m** & \(X\)**/m** & \(Y\)**/m** & \(Z\)**/m** & \\ \hline B1 & 551,379.119 & 2,915,387.696 & 1729.519 & 251,963.699 & 2,916,511.864 & 1766.708 & 0.031748 \\ B2 & 551,383.922 & 2,915,397.262 & 1729.033 & 251,968.764 & 2,916,521.269 & 1766.197 & 0.031388 \\ B3 & 551,516.047 & 2,915,430.586 & 1687.368 & 252,101.554 & 2,916,551.698 & 1724.605 & 0.045522 \\ B4 & 551,975.125 & 2,915,260.500 & 1654.448 & 252,557.497 & 2,916,368.768 & 1691.321 & 0.026318 \\ B5 & 551,980.360 & 2,915,270.591 & 1656.444 & 252,562.979 & 2,916,378.712 & 1693.298 & 0.014648 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Point cloud rough registration by unified coordinate system method. Figure 8: Control target point cloud coordinate query. and deviation, which ensured data integrity while effectively ensuring data accuracy. This laid a foundation for later analysis, as shown in Figure 9.  
For the fused point cloud, the error in fusion was counted by intelligent sampling. The smaller the distance between the nearest point pairs, the greater the number of fused point pairs, the lower the number of unfused point pairs, and the better the fusion quality, to test whether its accuracy meets the requirements. See Figure 10 for details.