View source: R/metrics_voxels.R
metrics_voxels | R Documentation |
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.
metrics_voxels(x, y, z, vox_size = 1, zmin = NA)
.metrics_voxels
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. |
An object of class formula
of length 2.
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.
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
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)
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