1. Detailed 3D quantification of tree structure plays a crucial role in understanding tree- and plot-level biophysical processes. Light detection and ranging (LiDAR) has led to a revolution in tree structural measurements and its 3D data are increasingly becoming publicly available. Yet, calculating structural metrics from LiDAR data can often be complex and time-consuming and potentially requires expert knowledge.
2. We present the R package Individual Tree Structural Metrics (ITSMe), a toolbox that works with LiDAR tree point clouds and quantitative structure models (QSMs) derived from LiDAR point clouds to obtain individual tree structural metrics. It serves as a robust synthesis framework for researchers who want to readily obtain structural information from 3D data of individual trees.
3. The package includes functions to determine basic structural metrics (tree height, diameter at breast height, diameter above buttresses, projected crown area, 3D alpha crown volume) from individual tree point clouds, as well as more complex structural metrics (individual tree component volumes, branch angle-, radius- and length-related metrics) from QSMs.
4. The ITSMe package is an open-source package hosted on GitHub that will make the use of 3D data more straightforward and transparent for a range of end-users interested in exploiting tree structure information.