voxels_counting: Voxels Counting
In rTLS: Tools to Process Point Clouds Derived from Terrestrial Laser Scanning

voxels_counting

R Documentation

Voxels Counting

Description

Creates cube like voxels of different size on a point cloud using the voxels function, and then return a summary_voxels of their features.

Usage

voxels_counting(
  cloud,
  edge_sizes = NULL,
  min_size,
  length_out = 10,
  bootstrap = FALSE,
  R = NULL,
  progress = TRUE,
  parallel = FALSE,
  threads = NULL
)

Arguments

`cloud`	A `data.table` with xyz coordinates of the point clouds in the first three columns.
`edge_sizes`	A positive `numeric` vector describing the edge length of the different cubes to perform. If `NULL`, it use edge sizes by default based on the largest range of XYZ and `min_size`.
`min_size`	A positive `numeric` vector of length 1 describing the minimum cube edge length to perform. This is required if `edge_sizes = NULL`.
`length_out`	A positive `interger` of length 1 indicating the number of different edge lengths to use. This is required if `edge_sizes = NULL`.
`bootstrap`	Logical. If `TRUE`, it computes a bootstrap on the H index calculations. `FALSE` as default.
`R`	A positive `integer` of length 1 indicating the number of bootstrap replicates. This need to be used if `bootstrap = TRUE`.
`progress`	Logical, if `TRUE` displays a graphical progress bar. `TRUE` as default.
`parallel`	Logical, if `TRUE` it uses a parallel processing for the voxelization. `FALSE` as default.
`threads`	An `integer` >= 0 describing the number of threads to use. This need to be used if `parallel = TRUE`.

Value

A data.table with the summary of the voxels created with their features.

Author(s)

J. Antonio Guzmán Q.

Examples


data(pc_tree)

#Applying voxels counting.
voxels_counting(pc_tree, min_size = 2)

#Voxels counting using bootstrap on the H indexes with 1000 repetitions.
voxels_counting(pc_tree, min_size = 2, bootstrap = TRUE, R = 1000)

rTLS documentation built on Jan. 19, 2026, 9:07 a.m.