modified PCA param section in vignette

vignettes/biodivMapR.Rmd

@@ -83,10 +83,13 @@ In this example, the spatial resolution of the input raster is 10m. Setting `win
 window_size = 10
 ```
 
-## PCA filtering
-If set to `TRUE`, a second filtering based on PCA outliers is processed.
+## PCA
+
+These parameters are related to the PCA method (`PCA` or `SPCA`, default is `SPCA`) and the filtering of PCA results.
+Set FilterPCA to `TRUE` if a second filtering based on PCA outliers is required.
 
-```{r PCA filtering}
+```{r PCA method and filtering}
+TypePCA = 'SPCA'
 FilterPCA = FALSE
 ```
 
@@ -146,7 +149,7 @@ Here is the code to perform PCA and select PCA bands:
 ```{r PCA}
 print("PERFORM PCA ON RASTER")
 PCA_Output        = perform_PCA(Input_Image_File, Input_Mask_File, Output_Dir,
-                               FilterPCA = TRUE, nbCPU = nbCPU,MaxRAM = MaxRAM)
+                               TypePCA = TypePCA, FilterPCA = TRUE, nbCPU = nbCPU,MaxRAM = MaxRAM)
 # path for the PCA raster
 PCA_Files         = PCA_Output$PCA_Files
 # number of pixels used for each partition used for k-means clustering
@@ -214,7 +217,6 @@ The following code computes $\alpha$ and $\beta$ diversity from field plots and
 
 ```{r alpha and beta diversity indices from vector layer}
 # location of the spectral species raster needed for validation
-TypePCA     = 'SPCA'
 Dir.Raster  = file.path(Output.Dir,basename(Input.Image.File),TypePCA,'SpectralSpecies')
 Name.Raster = 'SpectralSpecies'
 Path.Raster = file.path(Dir.Raster,Name.Raster)