bes_p_cushman: Configurational entropy for point patterns

In bespatial: Boltzmann Entropy for Spatial Data

Configurational entropy for point patterns

Description

Calculates Cushman's configurational entropy for point patterns (2021)

Usage

bes_p_cushman(x, nr_of_permutations, independent = FALSE)

Arguments

x	SpatRaster, stars, RasterLayer, RasterStack, RasterBrick, matrix, or array containing one or more rasters with one value and NAs
nr_of_permutations	Number of permutations performed on each input raster to calculate possible distribution of the number of nearest neighbors
independent	Should an independent set of permutations be performed for each input raster? TRUE/FALSE. Use FALSE (default) when each of your input rasters has the same configuration.

Value

A tibble

References

Cushman, S. A. (2021). Generalizing Boltzmann Configurational Entropy to Surfaces, Point Patterns and Landscape Mosaics. In Entropy (Vol. 23, Issue 12, p. 1616). MDPI AG. https://doi.org/10.3390/e23121616

Examples

  library(terra)
  library(bespatial)
  point_pattern = rast(system.file("raster/point_pattern.tif", package = "bespatial"))
  ce3 = bes_p_cushman(point_pattern, 100)
  plot(point_pattern, main = round(ce3$value, 2))
  ce3b = bes_p_cushman(point_pattern, 100, independent = TRUE)
  plot(point_pattern, main = round(ce3b$value, 2))

bespatial documentation built on April 3, 2025, 7:58 p.m.