R/varEVI.R

In RGISTools: Handling Multiplatform Satellite Images

#' Calculate the enhanced vegetation index (EVI)
#'
#' \code{varEVI} computes the enhanced vegetation index (EVI) from the 
#' blue, near-infrared (NIR) and red bands.
#'
#' The enhanced vegetation index (EVI) is a vegetation indicator that improves
#' the sensitivity towards high biomass densities compared to NDVI 
#' \insertCite{huete2002overview}{RGISTools} (See \code{\link{varNDVI}}). This
#' function is used within \code{\link{ls7FolderToVar}},
#' \code{\link{ls8FolderToVar}}, \code{\link{modFolderToVar}} and
#' \code{\link{senFolderToVar}}.
#'
#' @references \insertRef{huete2002overview}{RGISTools}
#'
#' @param blue a \code{raster} with the blue band of the capture.
#' @param red a \code{raster} with the red band of the capture.
#' @param nir a \code{raster} with the NIR band of the capture.
#' @param scfun a function to re-scale the original pixel values into 
#' reflectance (0-1).
#'
#' @return An EVI image in \code{raster} format.
#'
#' @examples
#' # path to the cropped and cutted MODIS images for the region of Navarre
#' wdir <- system.file("ExNavarreVar", package = "RGISTools")
#' # list all the tif files
#' files.mod <- list.files(wdir, pattern = "\\.tif$", recursive = TRUE, full.names = TRUE)
#' # print the MOD09 bands
#' getRGISToolsOpt("MOD09BANDS")
#' scale.factor <- 0.0001
#' 
#' # select the red, blue and nir bands
#' img.mod.red <- raster(files.mod[1]) * scale.factor
#' img.mod.blue <- raster(files.mod[3]) * scale.factor
#' img.mod.nir <- raster(files.mod[2]) * scale.factor
#' # calculate the EVI without scale
#' img.mod.evi <- varEVI(img.mod.blue, img.mod.red, img.mod.nir)
#' # calculate the EVI scaling 0-1
#' img.mod.evi.2 <- varEVI(img.mod.blue, img.mod.red, img.mod.nir,scfun=getRGISToolsOpt("MOD09SCL"))
#' img.mod.evi.12 <- stack(img.mod.evi,img.mod.evi.2)
#' # plot the image
#' spplot(img.mod.evi.12,col.regions=rev(terrain.colors(20)),at = c(seq(0,1,0.05)))
varEVI<-function(blue,red,nir,scfun=function(r){r}){
  blue=scfun(blue)
  red=scfun(red)
  nir=scfun(nir)
  evi <- 2.5*((nir - red) / (nir+6 * red-7.5*blue+1))
  return(evi)
}