In R I can easily compute the max/min value of each cell in a georeferenced raster stack using the max/min commands.
set.seed(42)
require(raster)
r1 <- raster(nrows=10, ncols=10)
r2=r3=r4=r1
r1[]= runif(ncell(r1))
r2[]= runif(ncell(r1))+0.2
r3[]= runif(ncell(r1))-0.2
r4[]= runif(ncell(r1))
rs=stack(r1,r2,r3,r4)
plot(rs)
max(rs)
min(rs)
However, I have been trying to find a way to find the second highest values across a stack. In my case, each raster on the stack denotes performance of a particular model across space. I would like to compare the first vs second best values to determine how much better is the best model from its runner up without having to convert my stack to a matrix and then back into a raster. Any ideas or suggestions??
max(rs[rs<max(rs)])
is one sloppy way. – Carl Witthoft