eigen_metrics: Calculates eigen decomposition metrics for fixed neighborhood...

In bi0m3trics/spanner: Utilities to support landscape-, forest-, and tree-related data analysis

Calculates eigen decomposition metrics for fixed neighborhood point cloud data

Description

This function calculates twelve (plus the first and second PCA) for several point geometry-related metrics (listed below) in parallel using C++ for a user-specified radius.

Usage

eigen_metrics(las = las, radius = 0.1, ncpu = 8)

Arguments

las	LAS Normalized las object.
radius	numeric the radius of the neighborhood
ncpu	integer the number of cpu's to be used in parallelfor the calculation

Value

A labeled data.table of point metrics for each point in the LAS object

List of available point metrics

\loadmathjax

• eLargest: first eigenvalue, \mjeqn\lambda_1ASCII representation

• eMedium: second eigenvalue, \mjeqn\lambda_2ASCII representation

• eSmallest: third eigenvalue, \mjeqn\lambda_3ASCII representation

• eSum: sum of eigenvalues, \mjeqn\sum_i=1^n=3 \lambda_iASCII representation

• Curvature: surface variation, \mjeqn\lambda_3 / \sum_i=1^n=3 \lambda_iASCII representation

• Omnivariance: high values correspond to spherical features and low values to planes or linear features, \mjeqn(\lambda_1 * \lambda_2 * \lambda_3)^1/3ASCII representation

• Anisotropy: relationships between the directions of the point distribution, \mjeqn(\lambda_1 - \lambda_3) / \lambda_1ASCII representation

• Eigentropy: entropy in the eigenvalues, \mjeqn- \sum_i=1^n=3 \lambda_i * ln(\lambda_i)ASCII representation

• Linearity: linear saliency, \mjeqn(\lambda_1 + \lambda_2) / \lambda_1ASCII representation

• Verticality: vertical saliency, \mjeqn1-abs(\langle (0,0,1),e_3\rangle)ASCII representation

• Planarity: planar saliency, \mjeqn(\lambda_2 + \lambda_3) / \lambda_1ASCII representation

• Nx,Ny,Nz: 3 components of the normal vector, ASCII representation

Examples

LASfile <- system.file("extdata", "MixedConifer.laz", package="lidR")
las <- readLAS(LASfile)
eigen = eigen_metrics(las, radius=2, ncpu=4)

bi0m3trics/spanner documentation built on June 9, 2025, 3:57 p.m.