Using mobile laser scanning in forest research

Background Mobile laser scanning (MLS) is increasingly arousing interest as a technique which provides valuable 3D-data for various applications in forest research. Using mobile platforms, the 3D-recording of large forest areas is carried out within a short space of time. However, for further analyses the successful extraction of single trees from the point cloud is essential. In our new study published in Annals of Botany we present a novel segmentation algorithm to automatically segment trees in MLS point clouds, applying distance adaptivity as a function of trajectory. In addition, tree parameters are determined simultaneously. In a test data set we found that the tree detection rate reached 96 % on average for trees with distances up to 45 m from the trajectory. Trees were almost completely segmented up to a distance of about 30 m from the MLS trajectory. When compared to data from terrestrial laser scanning (TLS) we observed that the accuracy of tree parameters was similar for MLS segmented and TLS segmented trees.

Conclusions Besides plot characteristics, the detection rate of trees in MLS data strongly depends on the distance to the travelled track. The algorithm presented in this study facilitates the acquisition of important tree parameters from MLS data, as an area-wide automated derivation can be accomplished in a very short time.

See more details in:

Bienert A, Georgi L, Kunz M, von Oheimb G, Maas HG, (2021). Automatic extraction and measurement of individual trees from mobile laser scanning point clouds of forests. Annals of Botany 128 (6): 787–804. https://doi.org/10.1093/aob/mcab087

A further study on the use of mobile laser scanning in forest research:

Bienert A, Georgi L, Kunz M, Maas HG, von Oheimb G, (2018). Comparison and combination of mobile and terrestrial laser scanning for natural forest inventories. Forests 9 (7): 395. DOI 10.3390/f9070395