grid_metrics3d
Voxelize the space and compute metrics for each voxel
Voxelize the cloud of points and compute a series of descriptive statistics for each voxel.
Usage
grid_metrics3d(.las, func, res = 1, debug = FALSE)
Arguments
- .las
An object of class
LAS
- func
the function to be apply to each voxel.
- res
numeric. The size of the voxels
- debug
logical. If you encounter a non trivial error try
debug = TRUE
.
Details
Voxelize 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. Basically there are no predefined metrics. Users must write their own function to create metrics. Voxelize will dispatch the LiDAR data for each voxel in the user's function. The user writes their function without considering voxels, only a cloud of points (see example).
Value
It returns a data.table
containing the metrics for each voxel. The table
has the class lasmetrics3d
enabling easier plotting.
See Also
Examples
# NOT RUN {
LASfile <- system.file("extdata", "Megaplot.laz", package="lidR")
lidar = readLAS(LASfile)
# Cloud of points is voxelized with a 1-meter resolution and in each voxel
# the number of points is computed.
grid_metrics3d(lidar, length(Z))
# Cloud of points is voxelized with a 1-meter resolution and in each voxel
# the mean scan angle of points is computed.
grid_metrics3d(lidar, mean(ScanAngle))
# Define your own metric function
myMetrics = function(i, angle, pulseID)
{
ret = list(
npulse = length(unique(pulseID)),
angle = mean(angle),
imean = mean(i)
)
return(ret)
}
voxels = grid_metrics3d(lidar, myMetrics(Intensity, ScanAngle, pulseID))
plot(voxels, "angle")
plot(voxels, "imean")
#etc.
# }