I would like to classify a raster map (SpatRaster) based on the attribute table attached to it, not the cell values.
Here is a reprex from the help of the terra::activeCat() function:
set.seed(0)
r <- rast(nrows=10, ncols=10)
values(r) <- sample(3, ncell(r), replace=TRUE) + 10
d <- data.frame(id=11:13, cover=c("forest", "water", "urban"), letters=letters[1:3], value=10:12)
levels(r) <- d
cats(r)
# [[1]]
# id cover letters value
# 11 forest a 10
# 12 water b 11
# 13 urban c 12
I would like to change cells with urban class (cover == "urban") into NA.
# this does not work
activeCat(r) <- 2
classify(r, cbind("urban", NA))
# this works but using the cell value
classify(r, cbind(13, NA))
Thanks
You can use subst
Example data
library(terra)
set.seed(0)
r <- rast(nrows=10, ncols=10)
values(r) <- sample(3, ncell(r), replace=TRUE) + 10
d <- data.frame(id=11:13, cover=c("forest", "water", "urban"), letters=letters[1:3], value=10:12)
levels(r) <- d
Solution
s <- subst(r, "urban", NA)
Although it is a bit odd to set a label to NA. So I would do this instead
ss <- subst(r, 13, NA, raw=TRUE)
Or the equivalent with classify that you show.
for more complex cases, you can remove the categories and then reset them later
cts <- cats(r)
levels(r) <- NULL
# do something with r
#
levels(r) = cts