Mask from raster with less RAM

Hi guys, thank you for your reply.

Jaime, I have tried, but I can't install rgdal needed to use raster and
apparently other people too (
https://stackoverflow.com/questions/57617895/how-to-install-rgdal-and-or-upload-raster-on-google-collaboration).
Do you have a solution?

Hugo, I need the mask in vector format because the rasters have different
resolutions, so I can't use raster as a mask. I have modified the reprex to
be more precise about it (see below).

Steve, I think this approach has the same issue of Hugo Costa. I don't have
the polygon of the mask, so I am trying to create one to apply in the other
rasters of different resolutions.

# reproducible example
library(raster)
# read data to create mask
r <- raster(system.file("external/test.grd", package="raster"))
r[!is.na(r)] <- 1
pol <- rasterToPolygons(r, dissolve = T) #  a lot of RAM to process the data
# raster of different resolution
res2 <- res(r) + 10
r2 <- raster(extent(r), resolution = res2)
r2[ ] <- 1
# apply the mask
r2.mask <- mask(r2, pol)
# plot
par(mfrow = c(1, 3))
plot(r)
plot(r2)
plot(r2.mask)

Cheers!

Em ter., 11 de ago. de 2020 ?s 19:26, Stephen Stewart <
stephen.stewart85 at gmail.com> escreveu:

Hi Frederico,

It may not solve all of your RAM issues, but in this situation I would
skip the rasterToPolygons (which is also usually very slow) and use raster
math to propagate NAs.

r <- raster(system.file("external/test.grd", package="raster"))
r[!is.na(r)] <- 1
# Can also be faster to do r = r / r, but add an offset (that cannot
result in 0) if you have valid 0s.
 r2 <- raster(extent(r), res(r))
r2[ ] <- 1
r2.mask <- r * r2

If you have a polygon to use as a mask, burn it in using the fasterize
package and then apply the above.

Hope that helps.

Cheers,

Steve

On Wed., 12 Aug. 2020, 6:43 am Frederico Faleiro, <fvfaleiro at gmail.com>
wrote:

Dear all,

I would like to generate a mask from a raster, but my workflow needs a lot
of RAM to process big rasters. I need this polygon mask to use in
another's
rasters.
Do you know another approach that needs less RAM?

# reproducible example
library(raster)
# read data to create mask
r <- raster(system.file("external/test.grd", package="raster"))
r[!is.na(r)] <- 1
pol <- rasterToPolygons(r, dissolve = T) #  a lot of RAM to process the
data
# apply the mask in another raster
 r2 <- raster(extent(r), res(r))
r2[ ] <- 1
r2.mask <- mask(r2, pol)

Cheers!

--
Frederico Faleiro
Postdoctoral Researcher in the INCT-EECBio (https://www.eecbio.ufg.br/)
Department of Ecology | Institute of Biological Science | Federal
University of Goi?s | Brazil
RG: https://www.researchgate.net/profile/Frederico_Faleiro
CV: http://lattes.cnpq.br/4926404840659003

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