Calculates the stem branch radius from a TreeQSM.
Usage
stem_branch_radius_qsm(
cylinder,
treedata,
normalisation = "treeheight",
pc = NA,
dtm = NA,
r = 5
)Arguments
- cylinder
Cylinder field of a TreeQSM that is returned by
read_tree_qsm.- treedata
Treedata field of a TreeQSM that is returned by
read_tree_qsm.- normalisation
Can be either "treeheight" or "parentcylinder". In case of "treeheight" the mean radius of the 10 biggest branches is divided by the tree height (Terryn et al., 2020). In case of "parentcylinder" the mean is taken of the ratios of the radius of the 10 biggest branches and the radius of their parent cylinders (Akerblom et al., 2017). When something different than "treeheight" or "parentcylinder" is given, no normalisation is done. Default is no normalisation.
- pc
The tree point cloud as a data.frame with columns X,Y,Z. Output of
read_tree_pc. Default is NA and indicates no tree point cloud is available. Only relevant if normalisation equals "treeheight".- dtm
The digital terrain model as a data.frame with columns X,Y,Z (default = NA). If the digital terrain model is in the same format as a point cloud it can also be read with
read_tree_pc. only relevant when a point cloud is provided.- r
Numeric value (default=5) r which determines the range taken for the dtm. Should be at least the resolution of the dtm. Only relevant when a dtm is provided.
Value
The stem branch radius. Unitless with normalisation, in meters without normalisation. NaN when there are no stem branches.
Details
The stem branch radius is defined as "Mean of the 10 largest 1st order
branches measured at the base. Can be normalised by the tree height or the
the stem radius at respective height" (Akerblom et al., 2017 & Terryn et al.,
2020). Tree height is calculated with tree_height.
References
Akerblom, M., Raumonen, P., Makipaa, R., & Kaasalainen, M. (2017). Automatic tree species recognition with quantitative structure models. Remote Sensing of Environment, 191, 1-12.
Terryn, L., Calders, K., Disney, M., Origo, N., Malhi, Y., Newnham, G., ... & Verbeeck, H. (2020). Tree species classification using structural features derived from terrestrial laser scanning. ISPRS Journal of Photogrammetry and Remote Sensing, 168, 170-181.
Examples
if (FALSE) {
# Read tree qsm and calculate the stem branch radius
# from Akerblom et al. (2017)
qsm <- read_tree_qsm(QSM_path = "path/to/qsm.mat")
sbr <- stem_branch_radius_qsm(
cylinder = qsm$cylinder,
treedata = qsm$treedata,
normalisation = "parentcyl"
)
# from Terryn et al. (2020)
sbr <- stem_branch_radius_qsm(
cylinder = qsm$cylinder,
treedata = qsm$treedata,
normalisation = "treeheight"
)
# with point cloud data
pc_tree <- read_tree_pc(PC_path = "path/to/point_cloud.txt")
sbr <- stem_branch_radius_qsm(
cylinder = qsm$cylinder,
treedata = qsm$treedata,
normalisation = "treeheight",
pc = pc_tree
)
}