Spatial Coverage Sampling

Generates sampling points at the centroids of compact geographical strata. This is purposive sampling designed for optimal spatial coverage.

Usage

ss_coverage(
  x,
  n_strata = NULL,
  prior_points = NULL,
  n_try = 1L,
  n_cells = 2500L,
  verbose = FALSE
)

Arguments

x

An sf object representing the study area, OR an ss_strata object from ss_stratify().

n_strata

Integer, number of strata (and samples) to create. Only used if x is an sf object.

prior_points

Optional sf object with prior sampling locations.

n_try

Integer, number of random initializations (default 1).

n_cells

Integer, approximate number of grid cells (default 2500).

verbose

Logical, whether to print progress (default FALSE).

Value

An object of class ss_samples containing:

samples

An sf object with sampling points at stratum centroids.

method

Character, "coverage".

n_samples

Integer, number of samples.

strata

The stratification object.

crs

The coordinate reference system.

Details

Spatial coverage sampling places sampling points at the centroids of compact geographical strata. This is optimal for model-based inference (kriging) as it provides even spatial coverage.

If a centroid falls outside the study area boundary, it is moved to the nearest cell center within the corresponding stratum.

See also

ss_stratify(), ss_random(), ss_stratified()

Examples

if (FALSE) { # \dontrun{
library(sf)
poly <- st_polygon(list(rbind(c(0, 0), c(100, 0), c(100, 50), c(0, 50), c(0, 0))))
study_area <- st_sf(geometry = st_sfc(poly))

# Direct usage
samples <- ss_coverage(study_area, n_strata = 25, n_try = 5)

# Or using pre-computed strata
strata <- ss_stratify(study_area, n_strata = 25, n_try = 5)
samples <- ss_coverage(strata)
} # }