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{sfnetworks} is an R package for analysis of geospatial networks. It connects and extends the functionalities of the {tidygraph} package for network analysis and the {sf} package for spatial data science.
Background
Geospatial networks are graphs embedded in geographical space. That means that both the nodes and edges in the graph can be represented as geographic features: the nodes most commonly as points, and the edges as linestrings. They play an important role in many different domains, ranging from transportation planning and logistics to ecology and epidemiology. The structure and characteristics of geospatial networks go beyond standard graph topology, and therefore it is crucial to explicitly take space into account when analyzing them.
We created {sfnetworks} to facilitate such an integrated workflow. It combines the forces of two popular R packages: {sf} for spatial data science and {tidygraph} for standard graph analysis. The core of the package is a dedicated data structure for geospatial networks, that can be provided as input to both the graph analytical functions of {tidygraph} as well as the spatial analytical functions of {sf}, without the need for conversion. Additionally, we implemented a set of geospatial network specific functions, such as routines for shortest path calculation, network cleaning and topology modification. {sfnetworks} is designed as a general-purpose package suitable for usage across different application domains, and can be seamlessly integrated in tidyverse workflows.
<picture> <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/luukvdmeer/sfnetworks/refs/heads/main/vignettes/figures/dependencies-dark.png"> <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/luukvdmeer/sfnetworks/refs/heads/main/vignettes/figures/dependencies.png"> <img alt="sfnetworks dependencies and building blocks." src="https://raw.githubusercontent.com/luukvdmeer/sfnetworks/refs/heads/main/vignettes/figures/dependencies.png"> </picture>Installation
You can install the latest stable version of {sfnetworks} from CRAN with:
install.packages("sfnetworks")
You can install the development version from GitHub with:
remotes::install_github("luukvdmeer/sfnetworks")
Note: Two important dependencies of {sfnetworks}, the {sf} package for spatial data science and the {igraph} package for network analysis (which is the main "analysis backend" of {tidygraph}), require some low-level software libraries to be installed on your system. Depending on which operating system you use, this can mean that you have to install these system requirements first, before you can install {sfnetworks}. See the installation guides of sf and igraph for details.
Usage
To get started with {sfnetworks}, read the Introduction to sfnetworks. Four additional package vignettes guide you in more detail through the functionalities of the package:
- Creating and representing spatial networks
- Cleaning spatial networks
- Spatial joins and filters
- Routing on spatial networks
Contribution
We look very much forward to contributions to the package. See the contributing guide for further details.
This project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
Acknowledgment
This project gratefully acknowledges financial support from the
<a href="https://www.r-consortium.org/all-projects/awarded-projects"> <img src="https://raw.githubusercontent.com/RConsortium/artwork/main/r_consortium/R_Consortium-logo-horizontal-color.png" width="300"> </a>