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Conditioned Latin Hypercube Sampling From a Raster Stack

Source: R/rf_optimization.R
ss_clhs_sample.Rd

Selects a representative baseline sample from a covariate raster stack using conditioned Latin hypercube sampling (cLHS). Typically used as the starting design for ss_rf_optimize().

Usage

ss_clhs_sample(covariates, n_samples, seed = NULL)

Arguments

covariates

A SpatRaster stack of environmental covariates.

n_samples

Integer, number of samples to select.

seed

Optional integer seed for reproducibility.

Value

A data frame with x, y and covariate columns for the selected sample locations.

See also

ss_rf_optimize(), ss_rf_size()

Examples

if (FALSE) { # \dontrun{
r <- terra::rast("data/predictors.tif")
samples <- ss_clhs_sample(r, n_samples = 100, seed = 123)
} # }