TY - JOUR
T1 - Analysing individual 3D tree structure using the R package ITSMe
AU - Terryn, Louise
AU - Calders, Kim
AU - Åkerblom, Markku
AU - Bartholomeus, Harm
AU - Disney, Mathias
AU - Levick, Shaun
AU - Origo, Niall
AU - Raumonen, Pasi
AU - Verbeeck, Hans
N1 - Funding Information:
L.T. was supported by special research fund (BOF) from Ghent University. M.D. acknowledges support of NERC National Centre for Earth Observation (NCEO).
Publisher Copyright:
© 2022 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.
PY - 2023/1
Y1 - 2023/1
N2 - 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. 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. 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. 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.
AB - 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. 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. 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. 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.
KW - LiDAR
KW - quantitative structure models
KW - R package
KW - tree structural metrics
U2 - 10.1111/2041-210X.14026
DO - 10.1111/2041-210X.14026
M3 - Article
AN - SCOPUS:85143830857
SN - 2041-210X
VL - 14
SP - 231
EP - 241
JO - Methods in Ecology and Evolution
JF - Methods in Ecology and Evolution
IS - 1
ER -