knitr::opts_chunk$set( collapse = TRUE, comment = "#>", eval=FALSE ) options(rmarkdown.html_vignette.check_title = FALSE)
This tutorial describes the processing workflow for biodivMapR
. It
goes through the different steps for the production of spectral
diversity maps using Sentinel-2 imagery. The workflow is divided into
three steps:
preprocS2
, which is a
wrapper of the rstac
and CDSE
packages.The default STAC collection is
sentinel-2-l2a
from the Planetary computer catalog.
biodivMapR
requires a raster / set of
raster as input data. The first biodivMapR v1
used spectral
transformations as initial pre-processing step. This included
reflectance normalization with a continuum removal, followed by a
spctral transformation (PCA, SPCA, MNF...).biodivMapR v2
now allows user to run the preprocessing step of their
choice. This can consist in computing spectral indices, vegetation
biophysical variables, or spectral transformation. This also means that
any type of input data can be used, as long as the input rasters share
the same footprint, spatial resolution and projection.
We provide a few examples here. Users can experiment with the method of their choice
Definition of the processing parameters This includes the following information:
Computation of the diversity maps This includes several diversity metrics:
Please refer to the branch dev_v1
of the package for the previous versions and tutorials.
Vignettes and tutorials corresponding to this version are still available here.
We recommend using the most-up-to-date versions of biodivMapR
, as the previous ones will not be maintained.
```{=html} <!-- * Comparison between spectral diversity metrics and ground observations
Below is the typical flow chart of the computation of diversity maps with biodivMapR :
Please check the full tutorial pages to get instructions, data and code examples to run biodivMapR
{target="_blank"} can be applied. -->
```
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