After two years of nighttime work, I am thrilled to announce the release of the fasterRaster package for R on CRAN!
fasterRaster is an R package designed specifically to handle large-in-memory/large-on-disk spatial rasters and vectors. fasterRaster does this using Open Source Geospatial’s GRASS GIS.
fasterRaster was created with five design principles:
- Value added: fasterRaster complements terra and sf, and is highly dependent on them! It is useful for analyzing large-in-memory/large-on-disk rasters and vectors that those packages struggle to handle. For medium- and small-size objects, terra and sf will almost always be faster.
- Familiarity: If you know how to use terra, you basically know how to use fasterRaster! That’s because most of the functions have the same name and almost the same arguments as terra functions.
- Comparability: To the degree possible, outputs from fasterRaster are the same as those from functions in terra with the same name.
- Simplicity: GRASS requires users to track things like “locations” or “projects”, “mapsets”, and “regions” for which there is no comparable analog in the terra or sf packages. fasterRaster handles these behind the scenes so you don’t need to.
- It’s R: The rgrass package provides a powerful conduit through which you can run GRASS modules from R. As such, it provides much more flexibility than fasterRaster. However, to use rgrass, you need to know what GRASS modules you want to use and be familiar with GRASS syntax. fasterRaster obviates this step but uses rgrass as a backend, allowing you to focus on R syntax and look up help for functions the normal way you do in R. You don’t need to know GRASS!
You can find out more on the fasterRaster website, which includes a tutorial on how to install and get started with fasterRaster!
