I am trying to plot only certain values from a categorical land cover raster I am working with. I have loaded it in to R using the terra package and it plots fine. However, since the original data did not come with a legend, I am trying to find out which raster value corresponds to what on the map.
Similar to the answer provided here: How to subset a raster based on grid cell values
I have tried using the following line:
> landcover
class : SpatRaster
dimensions : 20057, 63988, 1 (nrow, ncol, nlyr)
resolution : 0.0005253954, 0.0005253954 (x, y)
extent : -135.619, -102, 59.99989, 70.53775 (xmin, xmax, ymin, ymax)
coord. ref. : lon/lat WGS 84 (EPSG:4326)
source : spat_n5WpgzBuVAV3Ijm.tif
name : CAN_LC_2015_CAL_wgs
min value : 1
max value : 18
> plot(landcover[landcover == 18])
Error: cannot allocate vector of size 9.6 Gb
However, this line takes a very long time to run and produces a vector memory error. The object is 1.3 kb in the global environment and the original tif is about 300 mb.
You can use cats to find out which values correspond to which categories.
library(terra)
set.seed(0)
r <- rast(nrows=10, ncols=10)
values(r) <- sample(3, ncell(r), replace=TRUE) - 1
cls <- c("forest", "water", "urban")
levels(r) <- cls
names(r) <- "land cover"
cats(r)[[1]]
# ID category
#1 0 forest
#2 1 water
#3 2 urban
To plot a logical (Boolean) layer for one category, you can do
plot(r == "water")
And from from the above you can see that in this case that is equivalent to
plot(r == 1)