Create red-green-blue plot from a raster with RGB layers

This function takes as its main argument a GRaster with at least three layers typically representing red, green, and blue components (plus possibly an "alpha", or transparency layer). As with plot(), this function is somewhat of a hack in that it downsamples the layers to a coarser resolution using aggregate(), saves the raster to disk, then uses terra::plotRGB() to do the actual plotting.

Usage

# S4 method for class 'GRaster'
plotRGB(x, r = 1, g = 2, b = 3, a = NULL, simplify = TRUE, ...)

Arguments

x

A GRaster. Values must be in the range from 0 to 255.

r, g, b

Either a numeric integer or the names() of layers representing red, green, and blue components.

a

Either NULL (default), or a numeric integer or the names() of a layer representing transparency.

simplify

Logical: If TRUE (default), then downsample the GRaster before plotting. This can save time for very dense rasters.

...

Arguments to pass to terra::plotRGB().

Value

Nothing (makes a plot).

See also

terra::plotRGB(), plot(), compositeRGB()

Examples

if (grassStarted()) {

# Example data
madElev <- fastData("madElev") # elevation raster
madLANDSAT <- fastData("madLANDSAT") # multi-layer raster
madRivers <- fastData("madRivers") # lines vector

# Convert SpatRaster to GRaster and SpatVector to GVector
elev <- fast(madElev)
rivers <- fast(madRivers)
landsat <- fast(madLANDSAT)

# Plot:
plot(elev)
plot(rivers, add = TRUE)

# Histograms:
hist(elev)
hist(landsat)

# Plot surface reflectance in RGB:
plotRGB(landsat, 3, 2, 1) # "natural" color
plotRGB(landsat, 4, 1, 2, stretch = "lin") # emphasize near-infrared (vegetation)

# Make composite map from RGB layers and plot in grayscale:
comp <- compositeRGB(r = landsat[[3]], g = landsat[[2]], b = landsat[[1]])
grays <- paste0("gray", 0:100)
plot(comp, col = grays)

}