bes_m_cushman

Calculates Cushman's configurational entropy for landscape mosaics (2015)

Calculates several entropy metrics for spatial data
inspired by Boltzmann's entropy formula.
It includes metrics introduced by Cushman for landscape mosaics
(Cushman (2015) <doi:10.1007/s10980-015-0305-2>),
and landscape gradients and point patterns
(Cushman (2021) <doi:10.3390/e23121616>); by Zhao and Zhang for
landscape mosaics (Zhao and Zhang (2019) <doi:10.1007/s10980-019-00876-x>);
and by Gao et al. for landscape gradients
(Gao et al. (2018) <doi:10.1111/tgis.12315>; Gao and Li (2019) <doi:10.1007/s10980-019-00854-3>).

Jakub Nowosad

bespatial

Boltzmann Entropy for Spatial Data

bes_m_cushman function

<dl><dt>x</dt>
<dd>SpatRaster, stars, RasterLayer, RasterStack, RasterBrick, matrix, or array containing one or more categorical rasters</dd>
<dt>nr_of_permutations</dt>
<dd>Number of permutations performed on each input raster to calculate
possible distribution of total edge values</dd>
<dt>independent</dt>
<dd>Should an independent set of permutations be performed for each input raster?
<code>TRUE</code>/<code>FALSE</code>.
Use <code>FALSE</code> (default) when each of your input rasters has the same configuration (proportion of categories).</dd></dl>

Arguments

Configurational entropy for landscape mosaics — bes_m_cushman

<dl>

<dt>x</dt>
<dd>SpatRaster, stars, RasterLayer, RasterStack, RasterBrick, matrix, or array containing one or more categorical rasters</dd>


<dt>nr_of_permutations</dt>
<dd>Number of permutations performed on each input raster to calculate
possible distribution of total edge values</dd>


<dt>independent</dt>
<dd>Should an independent set of permutations be performed for each input raster?
<code>TRUE</code>/<code>FALSE</code>.
Use <code>FALSE</code> (default) when each of your input rasters has the same configuration (proportion of categories).</dd>

</dl>

bes_m_cushman: Configurational entropy for landscape mosaics

Description

Usage

Value

Arguments

References

Examples