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tin

Spatial Interpolation Algorithm


Description

This function is made to be used in grid_terrain or normalize_height. It implements an algorithm for spatial interpolation. Spatial interpolation is based on a Delaunay triangulation, which performs a linear interpolation within each triangle. There are usually a few points outside the convex hull, determined by the ground points at the very edge of the dataset, that cannot be interpolated with a triangulation. Extrapolation is done using the nearest neighbour approach.

Usage

tin(..., extrapolate = knnidw(3, 1, 50))

Arguments

...

unused

extrapolate

There are usually a few points outside the convex hull, determined by the ground points at the very edge of the dataset, that cannot be interpolated with a triangulation. Extrapolation is done using the nearest neighbour approach by default using knnidw.

See Also

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

Examples

LASfile <- system.file("extdata", "Topography.laz", package="lidR")
las = readLAS(LASfile, filter = "-inside 273450 5274350 273550 5274450")

#plot(las)

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

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

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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