Boltzmann entropy (also called configurational entropy) has been recently adopted to analyze entropy of landscape gradients (Gao et al. (2017), Gao et al. (2018)). The goal of belg is to provide an efficient C++ implementation of this method in R. It also extend the original idea by allowing calculations on data with missing values.
You can install the released version of belg from CRAN with:
install.packages("belg")And the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("Nowosad/belg")As an example, we use two small rasters - complex_land representing a
complex landscape and simple_land representing a simple landscape:
library(raster)
library(belg)
plot(stack(complex_land, simple_land))
The main function in this package, get_boltzmann, calculates the
Boltzmann entropy of a landscape gradient:
get_boltzmann(complex_land)
#> [1] 48.43241
get_boltzmann(simple_land)
#> [1] 18.3818This function accepts a RasterLayer, RasterStack, RasterBrick,
matrix, or array object as an input. It also allows for calculation
of the relative (the relative argument equal to TRUE) and absolute
Boltzmann entropy of a landscape gradient. As a default, it uses a
logarithm of base 10 (log10), however log and log2 are also
available options for the base argument.
get_boltzmann(complex_land, base = "log")
#> [1] 111.5198
get_boltzmann(complex_land, relative = TRUE)
#> [1] 35.50168
get_boltzmann(complex_land, base = "log2", relative = TRUE)
#> [1] 117.934- 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, Hong Zhang, and Zhilin Li. “A hierarchy-based solution to calculate the configurational entropy of landscape gradients.” Landscape Ecology 32(6) (2017): 1133-1146.