## 3 Result and Discussion Section
((**a**) shows the original point clouds; (**b**) shows the classification of ground points; (**c**) shows the filtering after classification of ground points). To verify the accuracy of the extracted single tree parameters, we conducted an accuracy analysis on the single wood parameters extracted by the laser SLAM scanner, lidar360 software and those extracted by manual measurement of the same tree, as shown in Figure 17. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**ID**} & \multirow{2}{*}{**X**} & \multirow{2}{*}{**Y**} & \multirow{2}{*}{**Tree Height**} & **DBH** & **Crown Diameter** & **Crown Area** & **Crown Volume** \\  & & & **(/m)** & **(/m)** & **(/m)** & **(/m\({}^{2}\))** & **(/m\({}^{3}\))** \\ \hline
1 & \(-\)6.639 & \(-\)23.901 & 9.157 & 0.26 & 6.753 & 35.82 & 152.966 \\ \hline
2 & \(-\)17.512 & \(-\)41.595 & 8.176 & 0.377 & 4.142 & 13.473 & 10.274 \\ \hline
3 & \(-\)14.129 & \(-\)45.489 & 13.973 & 0.281 & 7.054 & 39.083 & 137.76 \\ \hline
4 & \(-\)16.541 & \(-\)31.945 & 9.601 & 0.13 & 6.254 & 30.724 & 174.715 \\ \hline
5 & \(-\)12.915 & \(-\)17.261 & 8.824 & 0.181 & 5.85 & 26.879 & 131.372 \\ \hline  & \(\ldots\) & \(\ldots\) & \(\ldots\) & \(\ldots\) & \(\ldots\) & \(\ldots\) & \(\ldots\) \\ \hline
34 & \(-\)10.108 & \(-\)11.903 & 8.16 & 0.142 & 5.421 & 23.085 & 119.332 \\ \hline
35 & \(-\)11.635 & \(-\)47.423 & 13.084 & 0.121 & 5.829 & 26.683 & 155.889 \\ \hline
36 & \(-\)6.769 & \(-\)1.802 & 16.007 & 0.335 & 12.502 & 122.75 & 702.865 \\ \hline
37 & \(-\)7.792 & \(-\)4.054 & 7.746 & 0.22 & 3.379 & 8.965 & 34.196 \\ \hline
38 & \(-\)0.715 & \(-\)1.318 & 12.776 & 0.319 & 13.53 & 143.768 & 748.378 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Different parameters of single tree extraction. Figure 16: Single tree segmentation diagram. ((a) top view; (b) front view). When conducting the manual measurement, we used a standard measuring tape, and measure the tree's perimeter at 1.3 m around the height at the breast height position with an accuracy of 0.01 m. The tree's diameter at breast height was then calculated from the measured perimeter. The tree height was obtained by measuring the vertical angle and horizontal distance between the rhizome and the treetop in the same vertical direction using a total station. Taking the manual measurement value as the quasi-true value, we measured five trees separately and compared their accuracy with the point cloud tree parameters of Lidar360 software, and the analysis results are shown in Table 2.  
The results of the accuracy analysis in Table 2 show that the obtained plantation point clouds extracted by Lidar360 software after single wood segmentation have a difference of diameter at breast height: \(\leq\)\(\pm\)0.5 cm and tree height: \(\leq\)+10% or \(-\)20%, compared with the manually measured ones, which can be used for carbon storage estimation. We adopted the wood volume-derived biomass method in the sample plot inventory method to estimate the carbon storage of the plantation in the experimental area. According to the current standard of the \"Guidelines for Carbon Sinks Measurement and Monitoring in Afforestation Projects\" [30], the wood density of two tree species in the experimental area was calculated with reference to the national and IPCC carbon measurement parameters, i.e., camphor wood density is 0.460/tDM.m\({}^{3}\) and that for cypress is 0.478/tDM.m\({}^{3}\). According to the tree species classification method in the \"Main Technical Regulations of National Forest Resources Inventory\" and the allometric growth equation of national