explores performances of biodivMapR for different numbers of clusters

biodivMapR_OptClusters(
  input_raster,
  obs_vect,
  obs2optimize,
  SelectBands,
  obs_criterion = "shannon",
  input_mask = NULL,
  outputdir = "./",
  nbclusters = 50,
  MinSun = 0.25,
  nbIter = 20,
  pcelim = 0.02,
  verbose = T,
  nbRep = 50,
  maxPixel_kmeans = 1e+05,
  Hill_order = 1,
  algorithm = "Hartigan-Wong",
  nbCPU = 1
)

Arguments

input_raster: SpatRaster or list of SpatRaster
obs_vect: SpatVector or SpatVectorCollection
obs2optimize: numeric .list of ground obs diversity metrics corresponding to obs_vect. Expected values: richness, shannon, simpson, BC
SelectBands: numeric. bnds to select from input_raster
obs_criterion: character. richness, shannon, simpson or BC
input_mask: SpatRaster corresponding to mask
outputdir: character. output directory
nbclusters: numeric.
MinSun: numeric.
nbIter: numeric.
pcelim: numeric.
verbose: boolean.
nbRep: numeric.
maxPixel_kmeans: numeric.
Hill_order: numeric.
algorithm: character.
nbCPU: numeric.

Value

list including performances (correlation) of SFS with additional features and assessed diversity metrics corresponding to each step