Tutorial for biodivMapR

Jean-Baptiste Féret, Florian de Boissieu


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:

1 Processing parameters

1.1 Input / Output files

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.