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Point Cloud Decimation Algorithm


Description

These functions are made to be used in decimate_points. They implements algorithms that creates 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: homogenize(), random()

Other point cloud decimation algorithms: homogenize(), 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

Airborne LiDAR Data Manipulation and Visualization for Forestry Applications

v3.1.2
GPL-3
Authors
Jean-Romain Roussel [aut, cre, cph], David Auty [aut, ctb] (Reviews the documentation), Florian De Boissieu [ctb] (Fixed bugs and improved catalog features), Andrew Sánchez Meador [ctb] (Implemented wing2015() for segment_snags()), Bourdon Jean-François [ctb] (Contributed to Roussel2020() for track_sensor()), Gatziolis Demetrios [ctb] (Implemented Gatziolis2019() for track_sensor())
Initial release
2021-03-11

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