This tutorial aims at describing the processing workflow and giving the associated code to compute \(\alpha\) and \(\beta\) diversity maps on an extraction of Sentinel-2 image taken over Cameroun forest. The workflow is composed of the following steps:
define the processing parameters
validate results comparing to field plots measurements
The input images are expected to be in ENVI HDR format, BIL interleaved. The functions perform_radiometric_filtering
and perform_PCA
start with a procedure checkin if the image format is as expected. if not, the functions will retrun a message explaining the problem and will stop the process.
If the format is not ENVI format BIL interleaved, the function raster2BIL
allows conversion into proper format and returns updated Input_Image_File
Spectral bands should be defined if the image is multi or hyperspectral image.
A mask can also be set to work on a selected part of the input image. The mask is expected to be a raster in the same format as the image (ENVI HDR), with values 0 = masked or 1 = selected. Only one band is required. If no mask is to be used set Input_Mask_File = FALSE
.
The output directory defined with Output_Dir
will contain all the results. For each image processed, a subdirectory will be automatically created after its name.
Input_Image_File = system.file('extdata', 'RASTER', 'S2A_T33NUD_20180104_Subset', package = 'biodivMapR')
# Input.Image.File = raster2BIL(Raster.Path = Input.Image.File,
# Sensor = 'SENTINEL_2A',
# Convert.Integer = TRUE,
# Output.Directory = '~/test')
Input_Mask_File = FALSE
Output_Dir = 'RESULTS'
The image provided with the package is a subset of tile T33NUD acquired by Sentinel-2A satellite over Cameroonese rainforest in January 4th, 2018.