Question: 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?

Answer: 
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.

```
library(gdalUtils)
library(rgdal)

```

Build list of all raster files you want to join (in your current working directory).

```
all_my_rasts <- c('r1.tif', 'r2.tif', 'r3.tif')

```

Make a template raster file to build onto. Think of this a big blank canvas to add tiles to.

```
e <- extent(-131, -124, 49, 53)
template <- raster(e)
projection(template) <- '+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs'
writeRaster(template, file="MyBigNastyRasty.tif", format="GTiff")

```

Merge all raster tiles into one big raster.

```
mosaic_rasters(gdalfile=all_my_rasts,dst_dataset="MyBigNastyRasty.tif",of="GTiff")
gdalinfo("MyBigNastyRasty.tif")

```

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.
I have tested the solution using `gdalUtils` as proposed by *Matthew Bayly*. It works quite well and fast (I have about 1000 images to merge). However, after checking with document of `mosaic_raster` function [here](https://www.rdocumentation.org/packages/gdalUtils/versions/2.0.3.2/topics/mosaic_rasters), I found that it works without making a template raster before mosaic the images. I pasted the example codes from the document below:

```
outdir <- tempdir()
gdal_setInstallation()
valid_install <- !is.null(getOption("gdalUtils_gdalPath"))
if(require(raster) && require(rgdal) && valid_install)
{
layer1 <- system.file("external/tahoe_lidar_bareearth.tif", package="gdalUtils")
layer2 <- system.file("external/tahoe_lidar_highesthit.tif", package="gdalUtils")
mosaic_rasters(gdalfile=c(layer1,layer2),dst_dataset=file.path(outdir,"test_mosaic.envi"),
    separate=TRUE,of="ENVI",verbose=TRUE)
gdalinfo("test_mosaic.envi")

```

}