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rnaturalearth

An R package to hold and facilitate interaction with Natural Earth map data.

This package provides :

  • access to a pre-downloaded subset of Natural Earth v4.1.0 (March 2018) vector data commonly used in world mapping

  • easy subsetting by countries and regions

  • functions to download other Natural Earth vector and raster data

  • a simple, reproducible and sustainable workflow from Natural Earth data to rnaturalearth enabling updating as new versions become available

  • clarification of differences in world maps classified by countries, sovereign states and map units

  • consistency with Natural Earth naming conventions so that rnaturalearth users can use Natural Earth documentation

  • data in sf or sv formats

The Natural Earth website structures vector data by scale, category and type. These determine the filenames of downloads. rnaturalearth uses this structure to facilitate download (like an API).

Install rnaturalearth

Install from CRAN :

install.packages("rnaturalearth")

or install the development version from GitHub using devtools.

devtools::install_github("ropensci/rnaturalearth")

Data to support much of the package functionality are stored in two data packages that you will be prompted to install when required if you do not do so here.

devtools::install_github("ropensci/rnaturalearthdata")
devtools::install_github("ropensci/rnaturalearthhires")

First usage

Here using plot as a simple, quick way to plot maps. Maps could also be made with ggplot2, tmap or other options. All retrieval functions accept an argument returnclass = "sf" to return package sf (Simple Features) or returnclass = "sv" (SpatVector) objects.

library(rnaturalearth)

# world countries
plot(ne_countries())
Warning: plotting the first 10 out of 168 attributes; use max.plot = 168 to plot all
plot of chunk unnamed-chunk-2
plot of chunk unnamed-chunk-2

# uk
plot(ne_countries(country = "united kingdom"))
Warning: plotting the first 9 out of 168 attributes; use max.plot = 168 to plot all
plot of chunk unnamed-chunk-2
plot of chunk unnamed-chunk-2

# states, admin level1 boundaries
plot(ne_states(country = "spain"))
Warning: plotting the first 9 out of 121 attributes; use max.plot = 121 to plot all
plot of chunk unnamed-chunk-2
plot of chunk unnamed-chunk-2

Introductory vignette 

vignette("rnaturalearth", package = "rnaturalearth")

To download Natural Earth data not already in the package

There are a wealth of other data available at the Natural Earth website. rnaturalearth has functions to help with download of these data.

The data available are outlined in the two tables below and online here.


category   cultural

category   physical

Specify the scale, category and type of the vector you want as in the examples below.

# lakes
lakes110 <- ne_download(scale = 110, type = "lakes", category = "physical")
plot(lakes110)

# rivers
rivers50 <- ne_download(
  scale = 50,
  type = "rivers_lake_centerlines",
  category = "physical",
  returnclass = "sf"
)

library(ggplot2)
library(sf)

ggplot(rivers50) +
  geom_sf() +
  theme_minimal()

Details of different country definitions and scales 

vignette("what-is-a-country", package = "rnaturalearth")

Reproducible download of Natural Earth data into the package

Script used to get data into the accompanying data packages.

Errors in the data?

If you believe there is an issue with data provided by Natural Earth, please do not report it here. We are not responsible for the accuracy or maintenance of Natural Earth data. For any concerns regarding this data, please contact Natural Earth.

Acknowledgements

Thanks to Lincoln Mullen for code structure inspiration from USAboundaries, Hadley Wickham for comments and prompting, Bob Rudis for answers to stackoverflow questions about downloading Natural Earth data into R. The Natural Earth team and Nathan Kelso for providing such a great resource.

Potential future work

Potential additional data

Potential additional functions

  • facilitate joining of user data to country boundaries

  • facilitate subsetting by country groupings

    • e.g. least developed countries etc.