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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