maps alpha diversity indicators based on prior selection of PCs

map_alpha_div(
  Input_Image_File = FALSE,
  Input_Mask_File = FALSE,
  Output_Dir = "",
  window_size = 10,
  TypePCA = "SPCA",
  nbclusters = 50,
  MinSun = 0.25,
  pcelim = 0.02,
  Index_Alpha = "Shannon",
  FullRes = FALSE,
  LowRes = TRUE,
  MapSTD = TRUE,
  nbCPU = 1,
  MaxRAM = 0.25,
  ClassifMap = FALSE
)

Arguments

Input_Image_File

character. Path and name of the image to be processed.

Input_Mask_File

character. Path and name of the mask corresponding to the image to be processed.

Output_Dir

character. Output directory.

window_size

numeric. Size of spatial units (in pixels) to compute diversity.

TypePCA

character. Type of PCA (PCA, SPCA, NLPCA...).

nbclusters

numeric. Number of clusters defined in k-Means.

MinSun

numeric. Minimum proportion of sunlit pixels required to consider plot.

pcelim

numeric. Minimum contribution (in %) required for a spectral species.

Index_Alpha

character. Either 'Shannon', 'Simpson' or 'Fisher'.

FullRes

boolean. Full resolution.

LowRes

boolean. Low resolution.

MapSTD

boolean. map of standard deviation of the alpha diversity map (over repetitions)

nbCPU

numeric. Number of CPUs to use in parallel.

MaxRAM

numeric. MaxRAM maximum size of chunk in GB to limit RAM allocation when reading image file.

ClassifMap

character. If FALSE, perform standard biodivMapR based on SpectralSpecies. else corresponds to path for a classification map.

Value

None