Making fasterRaster faster

Adam B. Smith

2025-06-19

There are several ways to speed up fasterRaster functions. These are listed below in order of their most likely gains, with the first few being potentially the largest.

1. Load rasters and vectors directly from disk: Use fast() to load rasters and vectrors directly from disk. Converting terra or sf objects to GRasters and GVectors can be slower. Why? Because if the object does not have a file to which the R object points, Use fast() has to save it to disk first as a GeoTIFF or GeoPackage file, then load it into GRASS.

2. Save GRasters and GVectors directly to disk: Converting GRasters and GVectors to SpatRasters or SpatVector using rast() or vect(), then saving them is much slower than just saving them. Why? Because these functions actually save the file to disk then uses the respective function from the respective package to connect to the file.

3. Increase memory and the number of cores usable by GRASS: By default, fasterRaster use 2 cores and 2048 MB (2 GB) of memory for GRASS modules that allow users to specify these values. You can set these to higher values using faster() and thus potentially speed up some calculations. Functions in newer versions of GRASS have more capacity to use these options, so updating GRASS to the latest version can help, too.

4. Do operations on GRasters and GVectors in the same coordinate reference system together: Every time you switch between using a GRaster or GVector with a different coordinate reference system (CRS), GRASS has to spend a few seconds changing to that CRS. You can save some time by doing as much work as possible with objects in one CRS, then switching to work on objects in another CRS.

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