voxel_raster: Voxel raster summary function

In RCBlackburn/lidRmts: Area based lidar attributes

Voxel raster summary function

Description

This function provides individual voxel-based variables including the frequency ratio (FRDi),frequency ratio (FRSVi), number of returns below each sub-voxel (SVi) (PDiBelow), and the number of returns above each SVi (PDiAbove), sum of returns within a sub-voxels (SVsum), classifcation of a sub-voxel maximum (SVM), and median height of the number of returns above (SVMmdAbove) or within (SVMmd) SVMs. These variables are summarized within each pixel including the mean, median, variance, standard deviation, coefficient of variation, IQR, skewness, and kurtosis

Usage

voxel_raster(las, vox_res = vox_res, rast_res = rast_res, max_z)

Arguments

las	las object
vox_res	SVi cubic resolution in units of las object
rast_res	raster pixel resolution in units of las object
max_z	If numeric, the final height for all sub-voxels. If NULL, the max height for the entire point cloud (or chunk for catalog processing) will be used.

Value

returns a SpatRaster with 65 different layers representing voxel variables summarized to the resolution defined in (rast_res) with the naming convention: (voxel variable)_(voxel resolution)_(summary statistic)

Examples

LASfile <- system.file("extdata", "Megaplot.laz", package="lidR")
las <- readLAS(LASfile)
las <- filter_poi(las, Classification != LASNOISE)
las <- normalize_height(las, knnidw(k = 8, p = 2))
las <- filter_poi(las, Z < 50 & Z >= 1.37 )
las <- decimate_points(las, random_per_voxel(res = 1, n = 8))
metrics <- voxel_raster(las, vox_res = 2, rast_res = 10, max_z = 40)
plot(metrics)

RCBlackburn/lidRmts documentation built on Aug. 2, 2024, 11:21 a.m.