I've been trying to find a time-efficient way to merge multiple raster images in R. These are adjacent ASTER scenes from the southern Kilimanjaro region, and my target is to put them together to obtain one large image.
This is what I got so far (object 'ast14dmo' representing a list of RasterLayer objects):
# Loop through single ASTER scenes
for (i in seq(ast14dmo.sd)) {
if (i == 1) {
# Merge current with subsequent scene
ast14dmo.sd.mrg <- merge(ast14dmo.sd[[i]], ast14dmo.sd[[i+1]], tolerance = 1)
} else if (i > 1 && i < length(ast14dmo.sd)) {
tmp.mrg <- merge(ast14dmo.sd[[i]], ast14dmo.sd[[i+1]], tolerance = 1)
ast14dmo.sd.mrg <- merge(ast14dmo.sd.mrg, tmp.mrg, tolerance = 1)
} else {
# Save merged image
writeRaster(ast14dmo.sd.mrg, paste(path.mrg, "/AST14DMO_sd_", z, "m_mrg", sep = ""), format = "GTiff", overwrite = TRUE)
}
}
As you surely guess, the code works. However, merging takes quite long considering that each single raster object is some 70 mb large. I also tried Reduce and do.call, but that failed since I couldn't pass the argument 'tolerance' which circumvents the different origins of the raster files.
Anybody got an idea of how to speed things up?
I was faced with this same problem and I used
Although it did not produce a new merged raster file, it stored in the data environment and produced a merged map when plotted.
Or use do.call
or here, for the example in raster::merge
The 'merge' function from the Raster package is a little slow. For large projects a faster option is to work with gdal commands in R.
Build list of all raster files you want to join (in your current working directory).
Make a template raster file to build onto. Think of this a big blank canvas to add tiles to.
Merge all raster tiles into one big raster.
This should work pretty well for speed (faster than merge in the raster package), but if you have thousands of tiles you might even want to look into building a vrt first.
You can use
Reduce
like this for example :