View source: R/metrics_Terryn_2020.R
stem_branch_distance_qsm | R Documentation |
Calculates the stem branch distance from a TreeQSM.
stem_branch_distance_qsm(
cylinder,
treedata,
normalisation = "no",
pc = NA,
buttress = FALSE,
thresholdR2 = 0.001,
slice_thickness = 0.06,
thresholdbuttress = 0.001,
maxbuttressheight = 7,
concavity = 4,
dtm = NA,
r = 5
)
cylinder |
Cylinder field of a TreeQSM that is returned by
|
treedata |
Treedata field of a TreeQSM that is returned by
|
normalisation |
Can either be "dbh" or nothing. In case of "dbh" the average distance is divided by the DBH (Akerblom et al., 2017). |
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 distance is defined as "Average distance between 1st order
branches computed using a moving average with a window width 1 m. If window
is empty average distance in window is set as half of window width. Can be
normalised by the DBH" (Akerblom et al., 2017 & Terryn et al., 2020). When
something different than "dbh" is given, no normalisation is done. Default is
no normalisation. DBH is calculated with dbh
.
The stem branch distance. 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 distance
# from Akerblom et al. (2017)
qsm <- read_tree_qsm(QSM_path = "path/to/qsm.mat")
sbd <- stem_branch_distance_qsm(
cylinder = qsm$cylinder,
treedata = qsm$treedata,
normalisation = "dbh"
)
# with point cloud data for buttressed trees
pc <- read_tree_pc(PC_path = "path/to/point_cloud.txt")
sbd <- stem_branch_distance_qsm(
cylinder = qsm$cylinder,
treedata = qsm$treedata,
normalisation = "dbh", pc = tree_pc,
buttress = TRUE
)
# from Terryn et al. (2020)
sbd <- stem_branch_distance_qsm(
cylinder = qsm$cylinder,
treedata = qsm$treedata,
normalisation = "no"
)
## End(Not run)
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