# Comparison and Combination of Mobile and Terrestrial Laser Scanning for Natural Forest Inventories
## 7 Conclusions  
In this paper TLS data and MLS survey of a mixed natural forest in different seasons (leaf-off, leaf-on of deciduous trees) were compared with respect to their suitability for applications in forest inventories. The automatic tree detection of the TLS data showed a detection rate of 100% with three commission errors (plot 1) and 100% with 30 commission errors caused by understory trees (plot 2). In comparison, 87.5% of trees were detected in the MLS leaf-off dataset with eight commission errors (plot 1) and 100% of trees with 49 commission errors in plot 2. The DBHs determined with the method of the least squares cylinder fitting are derived from the QSM generation and show a RMSE of 1.1 cm for the TLS data and a RMSE of 3.7 cm for the MLS data. A slightly under-determined MLS tree height in comparison to the TLS tree height (precision: RMSE of 2.0 m of 7 trees measured with a Vertex IV) was detected. Also, the CPAs extracted from the MLS data are slightly under-estimated and show a RMSE of 2.9 m\({}^{2}\) and 2.2 m\({}^{2}\) in comparison to the CPAs attained from TLS data. As we compare the MLS to TLS forest parameters the precision of the estimated TLS forest parameters is essential. The precision of the used algorithm to estimate the volume from TLS data shows a slightly mean underestimation of 6% and a \(R^{2}\) of 0.90 compared to xylometric reference volumes in one of our previous studies [11]. The merchantable volume obtained from the QSMs show an underestimation of the data derived from MLS (RMSE 0.4 m\({}^{3}\) and 0.6 m\({}^{3}\)). The merchantable volume for smaller trees up to 1 m\({}^{3}\) fits very well with the volumes estimated from TLS measurements. Especially with the larger trees, enormous deviations of up to 5 m\({}^{3}\) for the total volume (RMSE 1.8 m\({}^{3}\)) were revealed due to occlusions in the crown space. The results presented here confirm that parameters derived from MLS point clouds such as tree position, DBH, tree height and CPA are similar to those obtained from TLS, and that the accuracies are within the range of precision required of forest inventory schemes. In future work, several plots along the trajectory will be processed and analyzed at different distances inside the 35 m corridor. MLS provides rapid and efficient covering of multiple large areas with multi-temporal recordings. The use of MLS in forest science is an emerging field of research. To facilitate a widespread use of MLS in forest research and inventories, future work should concentrate on developing methods for automatic individual tree segmentation and species identification of mixed forests on the basis of existing algorithms, as well as for the precise quantification of canopy space filling and spatio-temporal dynamics in tree-tree interactions for space in the canopy. All authors conceived and designed the experiments; [PERSON], [PERSON] and [PERSON] recorded the data. [PERSON] registered and analysed the TLS data; [PERSON] registered and analysed the MLS data; [PERSON] contributed data and analysis tools of the forest inventory parameters; [PERSON] and [PERSON] segmented the trees and extracted the QSM; [PERSON] and [PERSON] prepared the figures, [PERSON] wrote the paper; all authors contributed to manuscript revision and development. The work was supported by the German National Science Foundation (Deutsche Forschungsgemeinschaft, DFG 320926971) in the project \"Analysis of diversity effects on above-ground productivity in forests: advancing the mechanistic understanding of spatio-temporal dynamics in canopy space filling using mobile laser scanning\". We acknowledge support by the German Research Foundation and the Open Access Publication Funds of the SLUB/TU Dresden. **Acknowledgments:** We thank the forestry office of the city of Lubeck for providing inventory data and for permission to conduct this study in the Lauerholz Forest.