computes diversity metrics from validation plots

get_diversity_from_plots(
  input_rast,
  validation_vect,
  Kmeans_info,
  Beta_info = NULL,
  input_mask = NULL,
  selected_bands = NULL,
  rast_sample = NULL,
  alpha_metrics = c("richness", "shannon", "simpson", "hill"),
  Hill_order = 1,
  getBeta = TRUE,
  beta_metrics = c("bray", "brayturn", "jaccard", "jaccardturn", "sorensen",
    "simpson_diss"),
  fd_metrics = NULL,
  AttributeTable = NULL,
  min_sun = 0.25,
  pcelim = 0.02,
  nbCPU = 1,
  verbose = FALSE
)

Arguments

input_rast: SpatRaster
validation_vect: SpatVector
Kmeans_info: list. kmeans description obtained from function get_kmeans
Beta_info: list. BC dissimilarity & associated beta metrics from training set
input_mask: SpatRaster
selected_bands: numeric. bands selected from input_rast
rast_sample: dataframe.
alpha_metrics: character.
Hill_order: numeric. Hill order
getBeta: boolean. set true if computation of beta required
beta_metrics: character.
fd_metrics: character.
AttributeTable: dataframe.
min_sun: numeric. minimum amount of sunlit pixels in the plots
pcelim: numeric. minimum proportion of pixels to consider spectral species
nbCPU: numeric. Number of CPUs available
verbose: boolean. set true for messages

Value

SpatVector including diversity metrics and BC dissimilarity for the plots