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Voxel-based metrics

metrics_voxels.Rd

A set of metrics calculated in a voxel space, designed to be used within the pixel_metrics or cloud_metrics function from the lidR package. For convenience, a point cloud is converted to a voxel space on the fly, without the need of using additional processing steps. Note, that because of the additional computation required to convert a point cloud to voxels, calculating voxel-based metrics is markedly slower than other metrics_* functions.

Usage

metrics_voxels(x, y, z, vox_size = 1, zmin = NA)

.metrics_voxels

Format

An object of class formula of length 2.

Arguments

x, y, z

X, Y, Z coordinates of a point cloud to be converted into voxels

vox_size

voxel size

zmin

Minimum height. If set, heights below are ignored in calculations.

Details

Calculated metrics include:

  • vn count of filled voxels

  • FRall and FRcanopy: filled ratio. For FRall a ratio between the number of filled voxels and all voxels located in the maximum extent of the point cloud. For FRcanopy empty voxels above the canopy are excluded

  • metrics describing the vertical distribution of filled voxels: standard deviation (vzsd), coeficient of variation (vzcv), and vertical rumple (vzrumple).

  • Canopy volume classes based on Lefsky et al 1999 (see references), modified. A voxel representation of a forest stand is divided into four classes including: open gap space, closed gap space, euphotic zone, and oligophotic zone.

References

Lefsky, M. A., Cohen, W. B., Acker, S. A., Parker, G. G., Spies, T. A., & Harding, D. (1999). Lidar Remote Sensing of the Canopy Structure and Biophysical Properties of Douglas-Fir Western Hemlock Forests. Remote Sensing of Environment, 70(3), 339-361. doi:10.1016/S0034-4257(99)00052-8

Examples

library(lidR)
library(lidRmetrics)
LASfile <- system.file("extdata", "Megaplot.laz", package="lidR")
las <- readLAS(LASfile, select = "*", filter = "-keep_random_fraction 0.5")

m1 <- cloud_metrics(las, ~metrics_voxels(x = X, y = Y, z = Z, vox_size = 1))

m2 <- pixel_metrics(las, ~metrics_voxels(x = X, y = Y, z = Z, vox_size = 1), res = 20)