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Well, I had to do it in the most bizarre way I found, which was creating a 3D array, and saving it to PNG: m <- array(NA,c(nrow(country),ncol(country),3)) m[,,1] <- matrix(strtoi(paste('0x',substr(co …

I have a raster where 1 pixel = 1 byte. I want to change every value different than zero to 1, transforming a gray scale into black & white. …

library(raster) library(rgdal) r <- raster('gm_lc_v3.tif') p <- readOGR('ne_10m_admin_0_countries','ne_10m_admin_0_countries') i <- 66 # Dominican Republic country <- crop(r,p[i,]) png(paste(p$GEOUNIT[ … But since the margins are being added, my image is not representing the raster correctly. I want each pixel in the raster to become a pixel in the image. …

I've downloaded a countries shapefile from Natural Earth, and used it to clip GLC2000 raster using Brazil's border as the mask (in R). … setwd('~/R/GLC2000') library(rgdal) library(raster) glc <- raster('glc2000_v1_1') pa <- readOGR('.. …

My first thought was to convert the PNG (it's read as a three-layered matrix, for red, green and blue) to a raster. But creating a three-layered raster may be an overkill. …

The pixel colors come from a raster that describes the vegetation, and the boundaries of the countries come from a shapefile. … I managed to do almost all of it using the raster and rgdal libraries in R: library(raster) r <- raster('gm_lc_v3.tif') library(rgdal) p <- readOGR('ne_10m_admin_0_countries','ne_10m_admin_0_countries …

Worked with merge, only the colortable was missing: m3 <- merge(m1,m2) m3@legend@colortable <- m1@legend@colortable plot(m3) or m3 <- merge(m1,m2) m3@legend <- m1@legend plot(m3)

I have a 2x3 raster in R, with values 1 to 6. … library(raster) r <- raster(nrows=3,ncols=2,xmn=0,xmx=2,ymn=0,ymx=3,vals=1:6) colors <- c('red','orange','yellow','green','blue','purple') plot(r,col=colors) Now if I clip the raster, leaving the first …