Using a raster attribute from a multi-attribute raster for colour levels in a plot in R

Question

I have a raster object with a large number of attributes, and I would like to plot the spatial data in R and colour code it by a certain attribute. I have not been able to work out how to use the information of a particular attribute to achieve this. So far I have successfully extracted the attribute of choice using factorValues(), but I cannot determine how to now incorporate this information into the plot() function. I tried using the ratify() and level() functions mentioned in the raster package documentation, but I don’t understand how the simplified online examples can be adapted for a raster with multiple attributes.

Any advice on how to achieve this would be greatly appreciated.

# read in shapefile
shp = readOGR(".", "grid") 

#convert to raster
r = raster(extent(shp))
res(r) = c(1,0.5) 
ra = rasterize(shp, r)

#crop raster to desired extent
rcrop = crop(ra, extent(-12, 2, 29, 51))

# extract attribute value of interest 
f = factorValues(rcrop, 1:420, layer=1, att=17, append.names=FALSE)
# here there are 420 cells in the raster and I am interested in plotting values of attribute 17 of the raster (this is currently a numeric attribute, not a factor)

#extra code to set attribute as the level to use for plotting colours???
rcrop = ratify(rcrop)
rat = levels(rcrop)[[1]] #this just extras row IDs..not what I want
#…

### plot: I want to plot the grid using 7 colours (I would ideally like to specify the breaks myself)
require(RColorBrewer)
cols = brewer.pal(7,"YlGnBu")
#set breaks 
brks = seq(min(minValue(rcrop)),max(maxValue(rcrop),7))
#plot          
plot(rcrop, breaks=brks, col=cols, axis.arg=arg)

Answer 1

The following is pretty hacky (and may perform poorly for large rasters), but I'm not sure if there's a way to link col.regions to a specified attribute.

rasterVis::levelplot does a nice job of labelling colour ramps corresponding to factor rasters, and while it provides an att argument allowing you to specify which attribute you're interested in, this seems to only modify the labelling of the ramp. Raster cell values control how the colour ramp is mapped to the raster, so it seems to me that we need to modify the cell values themselves. Maybe @OscarPerpiñán will chime in here to prove me wrong :)

We can create a simple function to substitute the original cell values with whichever attribute we want:

switch_att <- function(r, att) {
  r[] <- levels(r)[[1]][values(r), att]
  r
}

Let's download and import a small example polygon dataset from Natural Earth:

library(rasterVis)
library(rgdal)
require(RColorBrewer)

download.file(file.path('http://www.naturalearthdata.com',
                        'http//www.naturalearthdata.com/download/110m/cultural',
                        'ne_110m_admin_0_countries.zip'),
              f <- tempfile())
unzip(f, exdir=tempdir())
shp <- readOGR(tempdir(), 'ne_110m_admin_0_countries')

rasterize the vector data:

r <- rasterize(shp, raster(raster(extent(shp), res=c(1, 1))))

And create some plots with levelplot:

levelplot(switch_att(r, 'continent'), col.regions=brewer.pal(8, 'Set2')) +
    layer(sp.polygons(shp, lwd=0.5))

levelplot(switch_att(r, 'economy'), par.settings=BuRdTheme) + 
  layer(sp.polygons(shp, lwd=0.5))

---

EDIT

With Oscar's update to rasterVis, the switch_att hack above is no longer necessary.

devtools::install_github('oscarperpinan/rastervis')
levelplot(r, att='continent', col.regions=brewer.pal(8, 'Set2')) + 
  layer(sp.polygons(shp, lwd=0.5))

will produce the same figure as the first one above.