sample_random: Point Cloud Decimation Algorithm

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

Point Cloud Decimation Algorithm

Description

This function is made to be used in decimate_points. It implements an algorithm that randomly removes points or pulses to reach the desired density over the whole area (see area).

Usage

random(density, use_pulse = FALSE)

Arguments

density	numeric. The desired output density.
use_pulse	logical. Decimate by removing random pulses instead of random points (requires running retrieve_pulses first)

See Also

Other point cloud decimation algorithms: sample_homogenize, sample_maxima, sample_per_voxel

Examples

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

# Reach a pulse density of 1 on the overall dataset
thinned1 = decimate_points(las, random(1))
plot(rasterize_density(las))
plot(rasterize_density(thinned1))

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