I am transferring a suitability model from arcpy into R, and am trying to find a function or package that performs a fuzzy overlay similar to FuzzyOverlay. What R operations would produce the same output as the fuzzyOverlay( , "AND") function in ArcPy?
My model produces intermediary raster layers with 0-100 values, which I am attempting to overlay through fuzzy membership
I've tried fuzzySim::fuzzyOverlay, but am not certain if these perform the same operation. My model inputs had values of 0-100, which ran fine in arcpy fuzzyOverlay, but fuzzySim::fuzzyOverlay gave an error until I rescaled values to 0-1. An attempt at reproducible code is below, but again, not certain if this is the function to be using.
#make 4 rasters
r1 <- raster(xmn = -100, xmx = -60, ymn = 25, ymx = 50, res = c(1,1))
r2 <- r1
r3 <- r1
r4 <- r1
#fill with random values
r1[] <- runif(ncell(r2), 0, 1)
r2[] <- runif(ncell(r2), 0, 1)
r3[] <- runif(ncell(r3), 0, 1)
r4[] <- runif(ncell(r3), 0, 1)
#stack rasters
rs <- stack(r1, r2, r3, r4)
#perform fuzzyOverlay
xy <- fuzzyOverlay(rs, op = "fuzzy_and")
I want an output that returns, per ESRI's description, "the minimum of the fuzzy memberships from the input fuzzy rasters", ideally in raster format. Am I on the right track?
Given the discriptions fuzzyAndValue = min(arg1, ..., argn)I think that is just a simple min function:
#make 4 rasters
r1 <- raster(xmn = -100, xmx = -60, ymn = 25, ymx = 50, res = c(1,1))
r2 <- r1
r3 <- r1
r4 <- r1
#fill with random values
r1[] <- runif(ncell(r2), 0, 1)
r2[] <- runif(ncell(r2), 0, 1)
r3[] <- runif(ncell(r3), 0, 1)
r4[] <- runif(ncell(r3), 0, 1)
#stack rasters
rs <- stack(r1, r2, r3, r4)
#perform fuzzyOverlay
xy <- min(rs)
plot(xy)