A set of R packages for handling and analysing spatial data, built upon OSGeo core libraries.

R-Spatial can be loosely defined as the ecosystem of code, projects and people using R for working with and adding value to spatial data. A manifestation of the wider R-Spatial community is the friendly, vibrant and diverse range of voices using the #rspatial tag on Twitter.

R-Spatial Open Source Community

As an open source community software project however, we define R-Spatial as the packages at r-spatial (sf, stars, mapview, gstat, spdep and many others) and rspatial (raster and terra).

Spatial Data Support in R

A good overview of Spatial Data support in R can be found at CRAN Task View: Analysis of Spatial Data. Another list with R packages that directly link to OSGeo libraries is found at R packages that use the OSGEO stack in System Requirements. Thousands of R packages depend on these packages.

Core features

  • Spatial Analysis

    • Raster and vector analysis
    • Geostatistics
    • Point pattern analysis
    • Spatial econometrics
    • Map creation
    • Spatial machine learning
  • Mapping

    • Enhanced interactive maps
    • High quality cartography
    • ggplot2-based maps
    • tmap-based maps
  • Raster analysis

    • Map algebra
    • Raster and vector data cubes
    • Handling out-of-memory datasets

Implemented Standards

  • Geographic JSON (GeoJSON)
  • Georeferenced Tagged Image File Format (GeoTIFF)
  • Keyhole Markup Language (KML)
  • Network Common Data Form (NetCDF)
  • OpenStreetMap (OSM)
  • Simple Features Access (SFA)
  • Simple Features for SQL (SFSQL)
  • Web Coverage Service (WCS)
  • Web Feature Service (WFS)
  • Well-Known Binary (WKB)
  • Well-Known Text (WKT)

The R packages involved are all on CRAN, which holds official releases and information about licenses. For instance, sf package description indicates a dual GPL-2 or MIT license