[GIS] R: aggregate raster with ‘mode’ function – how does it work

aggregationrraster

I want to aggregate a very fine resolution raster at various coarser resolutions (that represents many 1000s of categorical polygons).

The aggregate{raster} function is what i've traditionally used, the factor arguement reduces the resolution while the 'fun' allows me to sum, max or whatever.

However, when using fun=modal, how does aggregate behave? If I simply reduce the resolution by a factor of 2 (i.e. quarter the total number of cells) how does aggregate work with new multimodal cells?

example code:

ras <- raster(nrows=10, ncols=10,xmn=0, xmx=10, ymn=0, ymx=10)
ras[1:50] <- 1
ras[51:100] <- 2
x1 <- c(9,10,20,34,54,56,67,88,99)
ras[x1] <- NA
plot(ras)
grid(nx = 10, ny = 10, col = "lightgray", lty = "dotted",lwd = 1)

ras2 <- aggregate(ras,fact=2,expand=FALSE,fun=modal,na.rm=T)
x11()
plot(ras2)
grid(nx = 10, ny = 10, col = "lightgray", lty = "dotted",lwd = 1)

Ideally, when reducing by a factor, if there is a multimodal result I'd like aggregate to randomly assign the new cell one of the modal values and not always choose the same (if that's indeed what it does). Larger factors such as 5 etc are less likely to cause this issue but it is still entirely possible.

FURTHERMORE: in the aggregate function above, na.rm is set to TRUE because i dont want every single NA cell to set the new, coarser, cell automatically to NA. However in the top right of the data, that new cell should really be NA as it has 3 smaller NA values. Do i just need to re-assign NA to 999 before running? and how will it work if there are 2 NA cells and 2 cells of another value?

Best Answer

Ideally, when reducing by a factor, if there is a multimodal result I'd like aggregate to randomly assign the new cell one of the modal values and not always choose the same (if that's indeed what it does).

That is not what it does. See ?modal and the ties argument.

Your question is really about the modal function which you pass on to aggregate (both in package raster). So read the help file of modal and pick the arguments you like to make it behave how you want it to. If you cannot do that, find a better one elsewhere, or write your own.

The default behavior of modal is to break ties randomly, as illustrated here:

set.seed(9)
table(sapply(1:1000, function(i) modal(c(1,1,2,2))))

#  1   2 
#507 493

You have a further question about na.rm stating that

in the top right of the data, that new cell should really be NA as it has 3 smaller NA values.

I suppose you mean is that there are 3 NAs and 1 1 such that NA should be the mode. Perhaps that should be allowed as an option, but currently NA itself cannot be the modal value. The workaround you propose should be OK.

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