Background map | the R Graph Gallery

Input format and Package overview

R is an great tool for geospatial data analysis. Heaps of dedicated packages exist. Building a map follows those 2 steps:

Find data, load it in R: region boundaries can be stored in shapefiles or geoJSON files. Some R libraries also provide the data for the most common places. It is also possible to use google map style backgrounds.

Manipulate and plot it: once geo data are loaded in R you get a geospatial object that has specific features. You can manipulate it and plot it with packages like sp or ggplot2

Overview of input data and packages for doing maps in R

The Leaflet package for interactive maps

The leaflet R package is a wrapper of the Javascript leaflet.js library. It allows to build stunning interactive maps in minutes with R. Maps can be exported and standalong html files, or be embeded in a R markdown file or a shiny application. This great online course is dedicated to leaflet.

Most basic

The most basic background map you can do with R and the leaflet package. Default options only.

Zoom and Location

Learn how to zoom on a specific part of the map with the setView function.

Change tile

Several background tiles are offered by leaflet. Learn how to load them, and check the possibilities.

Leaflet maps are interactive: try to zoom and drag.

See Code

The ggmap package for static maps with background tiles

The ggmap library makes it easy to retrieve raster map tiles from popular online mapping services like Google Maps , OpenStreetMap or Stamen Maps, and plot them using the ggplot2 framework. It produces static maps like these. Click on an image to get the related code snippet.

Most basic

The most basic background map you can do with R and the ggmap package

Satellite

Apply the satellite background to the map

Roadmap

Apply the roadmap background to the map

Hybrid

Apply the hybrid background to the map

Stamen

Stamen is another tile provider, famous for this watercolour tile.

maps, mapdata and oz to get the most common boundaries

A few libraries provide the most common spatial objects. It avoids the struggle to find the information somewhere on the web. Maps library: Canada, France, Italy, USA and its regions, world cities, NZ. Mapdata library (China, Japan, NZ, World in High resolution) and the oz library (Australia).

World

USA

France

New Zealand

See all countries

sf to read shapefiles and .geojson files

If you are not satisfied with the previous options, you can search the web to find the spatial object you need. This information will most likely be stored under one of these two following formats, and can be read with the sf package:

shape file, as described here.
geojson file, as explained here.

Read and plot Shapefiles

learn how to read and plot shapefiles thanks to the sf package.

Read and plot geoJSON files

learn how to read and plot geoJSON files thanks to the sf package.

Geospatial data manipulation

Once you've got your geospatial data loaded into R, you are ready to manipulate it. Examples below show how to select a region, how to simplfy the boundaries to get a lighter object, how to compute the region centroids and more.

Select

How to select one or several regions in a geospatial object, and plot it.

Simplify

Simplifying a geospatial object allows to get a lighter object that will be plotted faster.

Centroid

Computing region centroids is a common task: it allows to add region labels afterwards.