nlm_randomcluster: nlm_randomcluster
In NLMR: Simulating Neutral Landscape Models

Description Usage Arguments Details Value References Examples

Simulates a random cluster nearest-neighbour neutral landscape.

nlm_randomcluster(
  ncol,
  nrow,
  resolution = 1,
  p,
  ai = c(0.5, 0.5),
  neighbourhood = 4,
  rescale = TRUE
)

`ncol`	[`integer(1)`] Number of columns forming the raster.
`nrow`	[`integer(1)`] Number of rows forming the raster.
`resolution`	[`numerical(1)`] Resolution of the raster.
`p`	[`numerical(1)`] Defines the proportion of elements randomly selected to form clusters.
`ai`	Vector with the cluster type distribution (percentages of occupancy). This directly controls the number of types via the given length.
`neighbourhood`	[`numerical(1)`] Clusters are defined using a set of neighbourhood structures, 4 (Rook's or von Neumann neighbourhood) (default), 8 (Queen's or Moore neighbourhood).
`rescale`	[`logical(1)`] If `TRUE` (default), the values are rescaled between 0-1.

This is a direct implementation of steps A - D of the modified random clusters algorithm by Saura & Martínez-Millán (2000), which creates naturalistic patchy patterns.

Raster with random values ranging from 0-1.

Saura, S. & Martínez-Millán, J. (2000) Landscape patterns simulation with a modified random clusters method. Landscape Ecology, 15, 661 – 678.

# simulate random clustering
random_cluster <- nlm_randomcluster(ncol = 30, nrow = 30,
                                     p = 0.4,
                                     ai = c(0.25, 0.25, 0.5))
## Not run: 
# visualize the NLM
landscapetools::show_landscape(random_cluster)

## End(Not run)