bes_g_gao {bespatial}

Boltzmann entropy of a landscape gradient

Description

Calculates the Boltzmann entropy of a landscape gradient by Gao (2017, 2019)

Usage

bes_g_gao(
  x,
  method = "aggregation",
  na_adjust = TRUE,
  base = "log10",
  relative = FALSE
)

Arguments

x

SpatRaster, stars, RasterLayer, RasterStack, RasterBrick, matrix, or array.

method

A method used. Either "hierarchy" for the hierarchy-based method (Gao et al., 2017) or "aggregation" (default) for the aggregation-based method (Gao et al., 2019).

na_adjust

Should the output value be adjusted to the proportion of not missing cells? Either TRUE (default) or FALSE

base

A logarithm base ("log", "log2" or "log10").

relative

Should a relative or absolute entropy be calculated? TRUE or FALSE (default).

Details

The method for computing the Boltzmann entropy of a landscape gradient works on integer values that are either positive or equals to zero. This function automatically rounds values to the nearest integer value (rounding halfway cases away from zero) and negative values are shifted to positive values.

Value

A tibble

References

Gao, Peichao, Hong Zhang, and Zhilin Li. "A hierarchy-based solution to calculate the configurational entropy of landscape gradients." Landscape Ecology 32.6 (2017): 1133-1146.

Gao, Peichao, Hong Zhang, and Zhilin Li. "An efficient analytical method for computing the Boltzmann entropy of a landscape gradient." Transactions in GIS (2018).

Gao, Peichao and Zhilin Li. "Aggregation-based method for computing absolute Boltzmann entropy of landscape gradient with full thermodynamic consistency" Landscape Ecology (2019)

Examples

library(terra)
library(bespatial)
gradient = rast(system.file("raster/gradient.tif", package = "bespatial"))
gg1 = bes_g_gao(gradient)
plot(gradient, main = round(gg1$value, 2))