maps functional diversity indicators based on prior selection of PCs

map_functional_div(
  Original_Image_File,
  Functional_File = FALSE,
  Selected_Features = FALSE,
  Output_Dir,
  window_size,
  TypePCA = "SPCA",
  MinSun = 0.25,
  FullRes = FALSE,
  LowRes = TRUE,
  MapSTD = TRUE,
  nbCPU = 1,
  MaxRAM = 0.25,
  SmoothImage = TRUE,
  FDmetric = c("FRic", "FEve", "FDiv")
)

Arguments

Original_Image_File: character. Path and name of the original input image for biodivMapR.
Functional_File: character. Path and name of the image processed to be used to compute functional diversity --> can be PCA file with. if FALSE: using Original_Image_File
Selected_Features: numeric. Contains features to be used from Input_Image_File. using all if FALSE
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...).
MinSun: numeric. Minimum proportion of sunlit pixels required to consider plot.
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.
SmoothImage: boolean. set TRUE if you want smooting filter applied to resulting diversity rasters
FDmetric: character. Functional diversity metric

Value

None