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kriging

Spatial Interpolation Algorithm


Description

This function is made to be used in grid_terrain or classify_ground. It implements an algorithm for spatial interpolation. Spatial interpolation is based on universal kriging using the krige function from gstat. This method combines the KNN approach with the kriging approach. For each point of interest it kriges the terrain using the k-nearest neighbour ground points. This method is more difficult to manipulate but it is also the most advanced method for interpolating spatial data.

Usage

kriging(model = gstat::vgm(0.59, "Sph", 874), k = 10L)

Arguments

model

A variogram model computed with vgm. If NULL it performs an ordinary or weighted least squares prediction.

k

numeric. Number of k-nearest neighbours. Default 10.

See Also

Other spatial interpolation algorithms: knnidw(), tin()

Examples

## Not run: 
LASfile <- system.file("extdata", "Topography.laz", package="lidR")
las = readLAS(LASfile)

# plot(las)

dtm = grid_terrain(las, algorithm = kriging())

plot(dtm, col = terrain.colors(50))
plot_dtm3d(dtm)

## End(Not run)

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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