This function creates a histogram of values in GRaster. The function is modeled after graphics::hist(), but actually uses graphics::barplot().
# S4 method for GRaster
hist(x, layer, maxnl = 16, bins = 30, freq = TRUE, ...)A named list of data.frames (invisibly), one per layer plotted, and creates a graph.
A GRaster.
Character, numeric, or integer: Indicates which layer of a multi-layer GRaster for which to plot a histogram. The layer can be identified using its name() (character) or index (numeric or integer). If this is missing, then up to maxnl layers are plotted.
Maximum number of layers for which to create histograms. This is 16 by default, but ignored if layer is defined.
Positive numeric integer: Number of bins in which to divide values of a raster with continuous values. For integer and categorical rasters, each value is tallied.
Logical: If TRUE (default), plot the frequency of values. If FALSE, plot the density of values (i.e., the number in each bin divided by the total number of cells with non-NA values).
Arguments to pass to graphics::barplot().
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)
}
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