LayerStacking: Individual Tree Detection Algorithm

In Jean-Romain/lidRplugins: Extra functions and algorithms for lidR package

Individual Tree Detection Algorithm

Description

This function is made to be used in find_trees. It implements the LayerStacking algorithm for tree detection based on Ayrey et al (2017) (see references). This function implements only the fisrt part of the method i.e. the detection of the trees.

Usage

LayerStacking(
  start = 0.5,
  res = 1,
  ws1 = 3,
  ws2 = 1.5,
  buf_size = 0.5,
  hardwood = FALSE,
  hmin = 2
)

Arguments

start	scalar The point cloud is horizontally layered at 1-m intervals starting at 'start' meters above the ground. Default is 0.5 (page 18)
res	scalar Resolution of the CHM computed with a point-to-raster approach. Default is 1 (page 19).
ws1	scalar Windows radius of the first local maxima use to detected tree tops on the CHM. Default is 3 (page 19)
ws2	scalar Windows radius of the second local maxima used to detected tree tops on the overlap map. Default is 1.5 (page 20)
buf_size	scalar Buffer size placed around each point to build a polygonal buffer around each cluster (figure 1c page 20). Default is 0.5 (page 18)
hardwood	logical. In dense conifer stands with little penetration to the center of the tree, additional weight on the overlap map is given to clusters (page 20). Default is FALSE
hmin	scalar. Point below this threshold cannot initiate a new tree.

References

Ayrey, E., Fraver, S., Kershaw, J. A., Kenefic, L. S., Hayes, D., Weiskittel, A. R., & Roth, B. E. (2017). Layer Stacking: A Novel Algorithm for Individual Forest Tree Segmentation from LiDAR Point Clouds. Canadian Journal of Remote Sensing, 43(1), 16–27. https://doi.org/10.1080/07038992.2017.1252907

See Also

Other individual tree detection algorithms: lmfauto(), multichm(), ptrees()

Jean-Romain/lidRplugins documentation built on Feb. 8, 2023, 5:39 a.m.