geom_features: Computes local geometrics features using a constant research...

In Blecigne/lidUrb: Terrestrial and Mobile Laser Scaning processing

Computes local geometrics features using a constant research distance

Description

Compute local geometric features of the point cloud based on the eigenvalues of the points covariance matrix. This function uses the python implementation provided in jakteristics.

Usage

geom_features(las, search_radius, features_list)

Arguments

las	a LAS file.
search_radius	numeric. The search distance to retrieve point neighborhood.
features_list	(optional) character. A vector containing the list of the geometric features to compute. Can be: "Eigenvalue_sum","Omnivariance", "Eigenentropy","Anisotropy","Planarity", "Linearity","PCA1","PCA2","Surface_variation","Sphericity","Verticality", "Nx","Ny","Nz".

Value

The LAS file with the geometric features added as new columns in the slot data. NOTE: the names of the features is a contraction of the feature name and search_radius.

Examples

# import data
file = system.file("extdata", "urban.las", package="lidUrb")
las = lidR::readLAS(file)

# compute all features
las = lidUrb::geom_features(las,search_radius = 0.1)

# plot Planarity and Linearity
lidR::plot(las,color="Planarity")
lidR::plot(las,color="Linearity")

Blecigne/lidUrb documentation built on Feb. 19, 2024, 9:12 a.m.