sample_per_voxel: Point Cloud Decimation Algorithm
In Jean-Romain/lidR: Airborne LiDAR Data Manipulation and Visualization for Forestry Applications
sample_per_voxel R Documentation
Point Cloud Decimation Algorithm
Description
This functions is made to be used in decimate_points. It implements an algorithm that
creates a 3D grid with a given resolution and filters the point cloud by randomly selecting
n points within each voxel
Usage
random_per_voxel(res = 1, n = 1)
Arguments
res
numeric. The resolution of the voxel grid used to filter the point cloud
n
integer. The number of points to select
See Also
Other point cloud decimation algorithms:
sample_homogenize,
sample_maxima,
sample_random
Examples
LASfile <- system.file("extdata", "Megaplot.laz", package="lidR")
las <- readLAS(LASfile, select = "xyz")
thinned <- decimate_points(las, random_per_voxel(8, 1))
#plot(thinned)
Jean-Romain/lidR documentation built on April 6, 2024, 9:41 p.m.
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| sample_per_voxel | R Documentation |
Point Cloud Decimation Algorithm
Description
This functions is made to be used in decimate_points. It implements an algorithm that creates a 3D grid with a given resolution and filters the point cloud by randomly selecting n points within each voxel
Usage
random_per_voxel(res = 1, n = 1)
Arguments
res |
numeric. The resolution of the voxel grid used to filter the point cloud |
n |
integer. The number of points to select |
See Also
Other point cloud decimation algorithms:
sample_homogenize,
sample_maxima,
sample_random
Examples
LASfile <- system.file("extdata", "Megaplot.laz", package="lidR")
las <- readLAS(LASfile, select = "xyz")
thinned <- decimate_points(las, random_per_voxel(8, 1))
#plot(thinned)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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