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R functions for processing individual tree TLS point clouds

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TreeLS

R functions for processing individual tree TLS point clouds.

Installation

devtools is required*

On the R console, enter: devtools::install_github('tiagodc/TreeLS')

Example

Load the package in the R environment.

require(TreeLS)

Two sample tree point clouds are provided: spruce and pine. To vizualize them:

rgl.points(pine, size=.5, col=cloud.col(pine, n=20))

Classification of trunk points can be done by 3 different methods: pref_HT, pref_SD and pref_VN. The fastest method is usually pref_HT.

trunk = pref_HT(pine)

#plot the trunk points
rgl.points(trunk, col='green')

#plot the rest of the tree
rgl.points(pine, size=.5)

Stem modelling is done over the previously extracted trunk points. Again, 3 methods can be used: fit_RANSAC_circle, fit_RANSAC_cylinder and fit_IRTLS. The fastest method is usually fit_RANSAC_circle.

stem = fit_RANSAC_circle(trunk)

#plot the stem model
mod = stem.model(stem, cyl.len=.3)

#plot the rest of the tree
rgl.points(pine, size=.5)

The output of the stem function is a list with two matrices: $stem.points, containing the stem point cloud, and $circles, containing estimations and statistics of modelled stem segments.

head(stem$stem.points)
print(stem$circles)

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R functions for processing individual tree TLS point clouds

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