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https://github.com/r-spatial/sf

Simple Features for R
https://github.com/r-spatial/sf

gdal geos proj r r-package rstats spatial

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Simple Features for R

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# Simple Features for R






A package that provides [simple features access](https://en.wikipedia.org/wiki/Simple_Features) for R. 



[Blogs, links](#blogs-presentations-vignettes-sp-sf-wiki) • [Cheatsheet](#cheatsheet) • [Installing](#installing)

• [Contributing](#contributing) • [Acknowledgment](#acknowledgment) • [How to cite](#how-to-cite)



Package sf:



* represents simple features as records in a `data.frame` or `tibble` with a geometry list-column

* represents natively in R all 17 simple feature types for all dimensions (XY, XYZ, XYM, XYZM)

* interfaces to [GEOS](https://libgeos.org) for geometrical operations on projected coordinates, and (through R package [s2](https://cran.r-project.org/package=s2)) to [s2geometry](http://s2geometry.io/) for geometrical operations on ellipsoidal coordinates

* interfaces to [GDAL](https://gdal.org/), supporting all driver options, `Date` and `POSIXct` and list-columns

* interfaces to [PRØJ](http://proj.org/) for coordinate reference system conversion and transformation

* uses [well-known-binary](https://en.wikipedia.org/wiki/Well-known_text#Well-known_binary) serialisations written in C++/Rcpp for fast I/O with GDAL and GEOS 

* reads from and writes to spatial databases such as [PostGIS](http://postgis.net/) using [DBI](https://cran.r-project.org/package=DBI)

* is extended by 

    * [lwgeom](https://github.com/r-spatial/lwgeom/) for selected liblwgeom/PostGIS functions

    * [stars](https://github.com/r-spatial/stars/) for raster data, and raster or vector data cubes (spatial time series)

    * [sfnetworks](https://luukvdmeer.github.io/sfnetworks/) for geospatial network data






(Illustration (c) 2018 by Allison Horst)



## Books, journal articles, blogs, presentations, vignettes, sp-sf wiki



* an open access [R Journal article](https://journal.r-project.org/archive/2018/RJ-2018-009/index.html) summarizes the package

* two books: [Spatial Data Science: with applications in R](https://r-spatial.org/book/), [Geocomputation with R](https://r.geocompx.org/)

* package vignettes: [first](https://r-spatial.github.io/sf/articles/sf1.html), [second](https://r-spatial.github.io/sf/articles/sf2.html), [third](https://r-spatial.github.io/sf/articles/sf3.html), [fourth](https://r-spatial.github.io/sf/articles/sf4.html), [fifth](https://r-spatial.github.io/sf/articles/sf5.html), [sixth](https://r-spatial.github.io/sf/articles/sf6.html), [seventh](https://r-spatial.github.io/sf/articles/sf7.html)

* blog posts: [first](https://r-spatial.org/r/2016/02/15/simple-features-for-r.html), [second](https://r-spatial.org/r/2016/07/18/sf2.html), [third](https://r-spatial.org/r/2016/11/02/sfcran.html), [fourth](https://r-spatial.org/r/2017/01/12/newssf.html)

* the original R Consortium ISC [proposal](PROPOSAL.md), the R Consortium [blog post](https://www.r-consortium.org/blog/2017/01/03/simple-features-now-on-cran)

* presentations: [rstudio::conf 2018](https://edzer.github.io/rstudio_conf/#1) ([video](https://posit.co/resources/videos/tidy-spatial-data-analysis/)), [UseR! 2016](http://pebesma.staff.ifgi.de/pebesma_sfr.pdf)

* wiki page describing [sp-sf migration](https://github.com/r-spatial/sf/wiki/Migrating)



## Cheatsheet

[CC 4.0](https://creativecommons.org/licenses/by/4.0/) BY [Ryan Garnett](https://github.com/ryangarnett)  






## Installing



Install either from CRAN with:

```r

install.packages("sf")

```

This will install binary packages on Windows and MacOS, unless you configured R such that it tries to install source packages; in that case, see below.



Install development versions from GitHub with:

```r

library(remotes)

install_github("r-spatial/sf")

```



### Windows



Installing sf from source works under Windows when [Rtools](https://cran.r-project.org/bin/windows/Rtools/) is installed.



### MacOS



MacOS users are strongly encouraged to install the `sf` binary packages from CRAN, unless they are familiar with compilers, linking, C++ source code, and homebrew.



The easiest way to install `gdal` is using Homebrew. Recent versions of Homebrew include a full-featured up-to-date [gdal formula](https://github.com/Homebrew/homebrew-core/blob/master/Formula/g/gdal.rb), which installs `proj` and `gdal` at the same time:



```

brew install pkg-config

brew install gdal

```



Once gdal is installed, you will be able to install `sf` package from source in R. With the current version of `proj` on homebrew, installation requires additional configuration:



```r

install.packages("sf", type = "source", configure.args = "--with-proj-lib=$(brew --prefix)/lib/")

```



Or the development version:



```r

library(remotes)

install_github("r-spatial/sf", configure.args = "--with-proj-lib=$(brew --prefix)/lib/")

```



If you are using `sf` and `rgdal` together, it is necessary to install `rgdal` from source using this configuration:



```r

install.packages("rgdal", type = "source", configure.args = c("--with-proj-lib=$(brew --prefix)/lib/", "--with-proj-include=$(brew --prefix)/include/"))

```



Alternatively, [these instructions](https://stat.ethz.ch/pipermail/r-sig-mac/2017-June/012429.html) explain how to install gdal using kyngchaos frameworks.



For Mac OS 11 Big Sur source install instruction, see [here](https://github.com/r-spatial/sf/issues/1536#issuecomment-727342736)



### Linux



For Unix-alikes, GDAL (>= 2.0.1), GEOS (>= 3.4.0) and Proj.4 (>= 4.8.0) are required.



#### Ubuntu



Dependencies for recent versions of Ubuntu (18.04 and later) are available in the official repositories; you can install them with:



```sh

apt-get -y update && apt-get install -y  libudunits2-dev libgdal-dev libgeos-dev libproj-dev

```



However, to get more up-to-date versions of dependencies such as GDAL, we recommend adding the [ubuntugis-unstable](http://ppa.launchpad.net/ubuntugis/ubuntugis-unstable/ubuntu/) PPA to the package repositories and installing them as follows:



```sh

sudo add-apt-repository ppa:ubuntugis/ubuntugis-unstable

sudo apt-get update

sudo apt-get install libudunits2-dev libgdal-dev libgeos-dev libproj-dev libsqlite0-dev

```



Adding this PPA is required for installing `sf` on older versions of Ubuntu (e.g. Xenial).



Another option, for advanced users, is to install dependencies from source; see e.g. an older [Travis](https://github.com/r-spatial/sf/blob/593ee48b34001fe3b383ea73ea57063ecf690732/.travis.yml) config file for hints.



#### Fedora

The following command installs all required dependencies:

```sh

sudo dnf install gdal-devel proj-devel geos-devel sqlite-devel udunits2-devel

```



#### Arch



Get gdal, proj, geos and podofo from the main repos, and udunits from the AUR:



```

pacman -S gdal proj geos arrow podofo

yay/pacaur/yaourt/whatever -S udunits

```



#### `renv` or `conda`



There are several reports that `sf` fails to install as a source package when R is used with `renv`, or when R is installed in a `conda` environment. If you experience this, please do not raise an issue here, but 



* try to sort this out with the `renv` developers or the `conda` maintainers, or

* try to use binary installs of the `sf` package, e.g. from [r2u](https://github.com/eddelbuettel/r2u), or the Posit package manager



#### Other



To install on Debian, the [rocker geospatial](https://github.com/rocker-org/geospatial) Dockerfiles may be helpful. Ubuntu Dockerfiles are found [here](https://github.com/r-spatial/sf/tree/main/inst/docker).



### Multiple GDAL, GEOS and/or PROJ versions on your system



If you use dynamic linking (installation from source) and have multiple versions of these libraries installed (e.g. one from ubuntugis-unstable, another installed from source in `/usr/local/lib`) then this will in general not work, even when setting `LD_LIBRARY_PATH` manually. See [here](https://github.com/r-spatial/sf/issues/844) for the reason why. 



### lwgeom



Functions and methods that require `liblwgeom`, including ellipsoidal (not spherical or Euclidean) metrics (area, distances), are provide by and used from [lwgeom](https://github.com/r-spatial/lwgeom), which is also on [CRAN](https://cran.r-project.org/package=lwgeom).



## Contributing



* Contributions of all sorts are most welcome, issues and pull requests are the preferred ways of sharing them.

* When contributing pull requests, please adhere to the package style (in package code use `=` rather than `<-`; don't change indentation; tab stops of 4 spaces are preferred).

* This project is released with a [Contributor Code of Conduct](CONDUCT.md). By participating in this project, you agree to abide by its terms.



## How to cite



Package `sf` can be cited as: 



* Edzer Pebesma, 2018.  Simple Features for R: Standardized Support

for Spatial Vector Data. The R Journal [10:1, 439-446.](https://journal.r-project.org/archive/2018/RJ-2018-009/index.html)



* Pebesma, E.; Bivand, R. (2023). [Spatial Data Science: With Applications in R](https://r-spatial.org/book/) 

(1st ed.). 314 pages. [Chapman and Hall/CRC](https://doi.org/10.1201/9780429459016).



## Acknowledgment



This project gratefully acknowledges financial [support](https://www.r-consortium.org/projects) from the