Within R, the terra and sf packages are the go-to solutions for geospatial analysis, but can struggle with rasters with many cells and vectors with many features. The standalone, open-source GRASS software allows efficient processing of large rasters and vectors. However, connecting to GRASS through R can be cumbersome and requires users to become familiar with GRASS-specific syntax, file organization, and data templates. I’m happy to announce the official publication of an article in Transactions in GIS detailing fasterRaster, the first user-friendly R package that allows users of R to harness the power of GRASS. terra and sf will nearly always be faster for processing of small- and medium-sized spatial objects, but for large objects, fasterRaster can be several times faster and enable processing where other solutions fail. A tutorial and documentation can be found on the pkgdown website, and code on the package’s GitHub repository.
fasterRaster: GIS in R using GRASS for large vectors and rasters [open-access preprint | article]
Smith, A.B. 2026. Transactions in GIS 30:70238.
