lidR (version 2.2.5)

voxel_metrics: Voxelize the space and compute metrics for each voxel

Description

This is a 3D version of grid_metrics. It creates a 3D matrix of voxels with a given resolution. It creates a voxel from the cloud of points if there is at least one point in the voxel. For each voxel the function allows computation of one or several derived metrics in the same way as the grid_metrics functions. The function will dispatch the LiDAR data for each voxel in the user's function (see grid_metrics).

Usage

voxel_metrics(las, func, res = 1)

Arguments

las

An object of class LAS.

func

formula. An expression to be applied to each voxel (see also grid_metrics).

res

numeric. The resolution of the voxels. res = 1 for a 1x1x1 cubic voxels. Optionally res = c(1,2) for non-cubic voxels (1x1x2 cuboid voxel).

Value

It returns a data.table containing the metrics for each voxel. The table has the class lasmetrics3d enabling easier plotting.

See Also

Other metrics: cloud_metrics(), grid_metrics(), hexbin_metrics(), point_metrics(), tree_metrics()

Examples

# NOT RUN {
LASfile <- system.file("extdata", "Megaplot.laz", package="lidR")
las = readLAS(LASfile)

# Cloud of points is voxelized with a 3-meter resolution and in each voxel
# the number of points is computed.
voxel_metrics(las, ~length(Z), 3)

# Cloud of points is voxelized with a 3-meter resolution and in each voxel
# the mean scan angle of points is computed.
voxel_metrics(las, ~mean(Intensity), 3)

# }
# NOT RUN {
# Define your own metric function
myMetrics = function(i)
{
  ret = list(
     npoints = length(i),
     imean   = mean(i)
   )

   return(ret)
}

voxels = voxel_metrics(las, ~myMetrics(Intensity), 3)

plot(voxels, color = "imean", trim = 100)
#etc.
# }