spsample-methods: Spatial Sampling of Compact Strata

In spcosa: Spatial Coverage Sampling and Random Sampling from Compact Geographical Strata

Spatial Sampling of Compact Strata

Description

Methods for sampling in compact strata.

Methods

x = "CompactStratification", n = "missing", type = "missing"

samples the centroids of each stratum.

x = "CompactStratification", n = "numeric", type = "missing"

stratified simple random sampling with n samples per stratum.

x = "CompactStratificationEqualArea", n = "numeric", type = "character"

if type = "composite", stratified simple random sampling of n composites.

x = "CompactStratificationPriorPoints", n = "missing", type = "missing"

spatial infill sampling

See Also

stratify for stratification, spsample for other types of spatial sampling, and estimate for inference. See the package vignette for more information and examples.

Examples

  # Note: the example below requires the 'sf'-package.
  ## Not run: 
    if (require(sf)) {
    
      # read a vector representation of the `Farmsum' field
      shpFarmsum <- as(st_read(
          dsn = system.file("maps", package = "spcosa"),
          layer = "farmsum"), "Spatial")
    
      # stratify `Farmsum' into 50 strata
      # NB: increase argument 'nTry' to get better results
      set.seed(314)
      myStratification <- stratify(shpFarmsum, nStrata = 50, nTry = 1)
    
      # sample two sampling units per stratum
      mySamplingPattern <- spsample(myStratification, n = 2)
    
      # plot the resulting sampling pattern on
      # top of the stratification
      plot(myStratification, mySamplingPattern)
    
    }
  
## End(Not run)

spcosa documentation built on Nov. 5, 2025, 5:10 p.m.