sample_maxima: Point Cloud Decimation Algorithm

In lidR: Airborne LiDAR Data Manipulation and Visualization for Forestry Applications

Point Cloud Decimation Algorithm

Description

These functions are made to be used in decimate_points. They implement algorithms that create a grid with a given resolution and filters the point cloud by selecting the highest/lowest point within each cell.

Usage

highest(res = 1)

lowest(res = 1)

Arguments

res	numeric. The resolution of the grid used to filter the point cloud

See Also

Other point cloud decimation algorithms: sample_homogenize, sample_per_voxel, sample_random

Other point cloud decimation algorithms: sample_homogenize, sample_per_voxel, sample_random

Examples

LASfile <- system.file("extdata", "Megaplot.laz", package="lidR")
las = readLAS(LASfile, select = "xyz")

# Select the highest point within each cell of an overlayed grid
thinned = decimate_points(las, highest(4))
#plot(thinned)

# Select the lowest point within each cell of an overlayed grid
thinned = decimate_points(las, lowest(4))
#plot(thinned)

lidR documentation built on Sept. 11, 2024, 5:21 p.m.