compute alpha and beta diversity metrics from pixel data corresponding to spectral species extracted from a window

compute alpha and beta diversity metrics from pixel data corresponding to spectral species extracted from a window

alphabeta_window(
  SSwindow,
  nb_clusters,
  Beta_info,
  alpha_metrics,
  beta_metrics,
  pcelim = 0.02,
  Hill_order = 1,
  diss_output = FALSE,
  p = NULL
)

Arguments

SSwindow

dataframe. spectral species corresponding to a raster subset (window = elementary spatial unit of process)

nb_clusters

numeric. number of clusters used in kmeans

Beta_info

list. BC dissimilarity & associated beta metrics

alpha_metrics

list. alpha diversity metrics

beta_metrics

list. beta diversity metrics

pcelim

numeric. min proportion of pixels to consider spectral species

Hill_order

numeric. Hill order

diss_output

boolean set TRUE to get dissimilarity matrices as outputs

p

list. progressor object for progress bar

Value

list of alpha and beta diversity metrics corresponding to SSwindow