nlm_mosaicgibbs

Simulate a neutral landscape model using the Gibbs algorithm introduced in Gaucherel (2008).

Usage

nlm_mosaicgibbs(
  ncol,
  nrow,
  resolution = 1,
  germs,
  R,
  patch_classes,
  rescale = TRUE
)

Arguments

ncol

[numerical(1)]
Number of columns forming the raster.

nrow

[numerical(1)]
Number of rows forming the raster.

resolution

[numerical(1)]
Resolution of the raster.

germs

[numerical(1)]
Intensity parameter (non-negative integer).

R

[numerical(1)]
Interaction radius (non-negative integer) for the fitting of the spatial point pattern process - the min. distance between germs in map units.

patch_classes

[numerical(1)]
Number of classes for germs.

rescale

[logical(1)]
If TRUE (default), the values are rescaled between 0-1.

Value

RasterLayer

Details

nlm_mosaicgibbs offers the second option of simulating a neutral landscape model described in Gaucherel (2008). The method works in principal like the tessellation method (nlm_mosaictess), but instead of a random point pattern the algorithm fits a simulated realization of the Strauss process. The Strauss process starts with a given number of points and uses a minimization approach to fit a point pattern with a given interaction parameter (0 - hardcore process; 1 - Poisson process) and interaction radius (distance of points/germs being apart).

References

Gaucherel, C. (2008) Neutral models for polygonal landscapes with linear networks. Ecological Modelling, 219, 39 - 48.

Examples

# simulate polygonal landscapes
mosaicgibbs <- nlm_mosaicgibbs(ncol = 40,
                              nrow = 30,
                              germs = 20,
                              R = 0.02,
                              patch_classes = 12)

if (FALSE) {
# visualize the NLM
landscapetools::show_landscape(mosaicgibbs)
}