View source: R/metrics_Terryn_2020.R
stem_branch_length_qsm | R Documentation |
Calculates the stem branch length from a TreeQSM.
stem_branch_length_qsm(
branch,
treedata,
normalisation = "treeheight",
pc = NA,
buttress = FALSE,
thresholdR2 = 0.001,
slice_thickness = 0.06,
thresholdbuttress = 0.001,
maxbuttressheight = 7,
concavity = 4,
dtm = NA,
r = 5
)
branch |
Branch field of a TreeQSM that is returned by
|
treedata |
Treedata field of a TreeQSM that is returned by
|
normalisation |
Can be either "dbh" or "treeheight". In case of "dbh" the mean of the lengths of the stem branches are divided by the DBH (Akerblom et al., 2017). In case of "treeheight" the mean is divided by the tree height (Terryn et al., 2020). When something different than "dbh" or "treeheight" 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
|
buttress |
Logical (default=FALSE), indicates if the trees have buttresses. Only relevant if pc is available and normalisation equals "dbh". |
thresholdR2 |
Numeric value (default=0.001). Parameter of the
|
slice_thickness |
Numeric value (default = 0.06). Parameter of the
|
thresholdbuttress |
Numeric value (default=0.001). Parameter of the
|
maxbuttressheight |
Numeric value (default=7). Parameter of the
|
concavity |
Numeric value (default=4) concavity for the computation of
the functional diameter using a concave hull based on
|
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 |
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. |
The stem branch length is defined as "the average length of 1st order
branches. Can be normalised by DBH or tree height" (Akerblom et al., 2017 &
Terryn et al., 2020). DBH and tree height are calculated with
dbh
and tree_height
.
The stem branch length. Unitless with normalisation, in meters without normalisation. NaN when there are no stem branches.
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.
## Not run:
# Read tree qsm and calculate the stem branch radius
# from Akerblom et al. (2017)
qsm <- read_tree_qsm(QSM_path = "path/to/qsm.mat")
sbl <- stem_branch_length_qsm(
branch = qsm$branch,
treedata = qsm$treedata,
normalisation = "dbh"
)
# with point cloud data for a buttressed tree
pc_tree <- read_tree_pc(PC_path = "path/to/point_cloud.txt")
sbl <- stem_branch_length_qsm(
branch = qsm$branch, treedata = qsm$treedata,
normalisation = "dbh", pc = pc_tree,
buttress = TRUE
)
# from Terryn et al. (2020)
sbl <- stem_branch_length_qsm(
branch = qsm$branch, treedata = qsm$treedata,
normalisation = "treeheight"
)
# with point cloud data
pc_tree <- read_tree_pc(PC_path = "path/to/point_cloud.txt")
sbl <- stem_branch_length_qsm(
branch = qsm$branch, treedata = qsm$treedata,
normalisation = "treeheight", pc = pc_tree
)
## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.