summary_voxels: Voxels Summary
In rTLS: Processing of Point Clouds Derived from Terrestrial Laser Scanning

summary_voxels

R Documentation

Voxels Summary

Description

Create a summary objects of class "voxels" created using the voxels.

Usage

summary_voxels(voxels, edge_length = NULL, bootstrap = FALSE, R = NULL)

Arguments

`voxels`	An object of class `voxels` created using the `voxels()` function or a `data.table` describing the voxels coordinates and their number of points produced using `voxels()`.
`edge_length`	A positive `numeric` vector with the voxel-edge length for the x, y, and z coordinates. This need to be used if `class(voxels) != "voxels"`. It use the same dimensional scale of the point cloud.
`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`.

Details

The function provides 12 main statistics of the voxels. Specifically, the first three columns represent the edge length of the voxels, the following three columns (ei. N_voxels, Volume, Surface) describe the number of voxels created, the total volume that they represent, and the surface area that they cover. Following columns represent the mean (Density_mean) and sd (Density_sd) of the density of points per voxel (e.g. points/m2). Columns 9:12 provide metrics calculated using the Shannon Index. Specifically, H describe the entropy, H_max the maximum entropy, Equitavility the ratio between H and Hmax, and Negentropy describe the product of Hmax - H. If bootstrap = TRUE four more columns are created (13:16). These represent the mean and sd of the H index estimated using bootstrap (H_boot_mean and H_boot_sd), the Equtavility_boot as the ratio of the ratio between H_boot_sd and Hmax, and Negentropy_boot as the product Hmax - H_boot_mean.

Value

A data.table with with the summary of voxels.

Author(s)

J. Antonio Guzmán Q.

Examples

data("pc_tree")

#Apply a summary on a object of class "voxels" using bootstrap with 1000 replicates.
vox <- voxels(pc_tree, edge_length = c(0.5, 0.5, 0.5))
summary_voxels(vox, bootstrap = TRUE, R = 1000)

#Apply a summary on a product from 'voxels' using bootstrap with 1000 replicates.
vox <- voxels(pc_tree, edge_length = c(0.5, 0.5, 0.5), obj.voxels = FALSE)
summary_voxels(vox, edge_length = c(0.5, 0.5, 0.5), bootstrap = TRUE, R = 1000)

rTLS documentation built on Dec. 28, 2022, 1:28 a.m.