sim_forest_cover: Simulating forest cover maps with defined covariance...
In AWF-GAUG/gsgsim: Gloabal Sampling Grid simulation framework

Description Usage Arguments Value Author(s) Examples

View source: R/map_sim.R

Simulating forest cover maps with defined covariance structure using random fields

1 2	sim_forest_cover(ras_dim, pxl_size, p, cov_model = NULL, alpha = 0.7, beta = 0.3, scale = floor(1/3 * sqrt((sum(ras_dim * pxl_size)^2))), ...)

`ras_dim`	A vector of two values where the first specifies the number of columns and the second the number of rows of the output raster.
`pxl_size`	Pixel size of the output map.
`p`	Forest cover of the out put map, 0 < p <= 1.
`cov_model`	A covariance model used for the random fields simulation. Type `RFgetModelNames(type="positive definite")` to get a list of available models. Defaults to `NULL` in which case a generalized cauchy family covariance model is used (`RMgencauchy`).
`alpha`	See `RMgencauchy`
`beta`	See `RMgencauchy`
`scale`	See `RMgencauchy`. Default value is set to on third of the main diagonal taken from `ras_dim` and `pxl_size`.
`...`	Other parameters used by `RMgencauchy`.

A binary raster map of simulated forest cover.

Paul Magdon, Sebastian Schnell

# Raster size
ras_dim <- c(1000, 1000);

# Pixel size
pxl_size <- 30;

# Forest cover
p <- 0.7;
# Cauchy covariance model
# 0 < alpha <= 2 - low alpha -> high fragmentation
# beta > 0 - smaller beta -> longer long-range dependence
cov_model <- RMgencauchy(alpha = 1.95,
                         beta = 0.3,
                         scale = 1/3*sqrt((sum(ras_dim*pxl_size)^2)));
forest_ras <- sim_forest_cover(ras_dim, pxl_size, cov_model, p);
plot(forest_ras);