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Working with shapefiles, projections and world maps in ggplot

In this post I will show some different examples of how to work with map projections and how to plot the maps using ggplot. Many maps that are shown using their default projection are in the longlat-format, which is far from optimal. For plotting world maps I prefer to use either Robinson or Winkel Tripel projection—but many more are available—and I will show how to use both these projections.

Before we get started you need to download a couple of shapefiles that we will use. You can find them here:

Put them directly inside your working directory. We will use functions from the rgdal-package to read the shapefiles into R, so if you do not have it, you need to install it before you continue. 

library(rgdal)
library(ggplot2)
setwd("/Users/kris/maps_ggplot")
 
# read shapefile
wmap <- readOGR(dsn="ne_110m_land", layer="ne_110m_land")
# convert to dataframe
wmap_df <- fortify(wmap)
 
# create a blank ggplot theme
theme_opts <- list(theme(panel.grid.minor = element_blank(),
                        panel.grid.major = element_blank(),
                        panel.background = element_blank(),
                        plot.background = element_rect(fill="#e6e8ed"),
                        panel.border = element_blank(),
                        axis.line = element_blank(),
                        axis.text.x = element_blank(),
                        axis.text.y = element_blank(),
                        axis.ticks = element_blank(),
                        axis.title.x = element_blank(),
                        axis.title.y = element_blank(),
                        plot.title = element_text(size=22)))
 
# plot map
ggplot(wmap_df, aes(long,lat, group=group)) + 
  geom_polygon() + 
  labs(title="World map (longlat)") + 
  coord_equal() + 
  theme_opts
 
ggsave("maps/map1.png",  width=12.5, height=8.25, dpi=72)

This will create a longlat-projected world map. World map in ggplot 

# reproject from longlat to robinson
wmap_robin <- spTransform(wmap, CRS("+proj=robin"))
wmap_df_robin <- fortify(wmap_robin)
ggplot(wmap_df_robin, aes(long,lat, group=group)) + 
  geom_polygon() + 
  labs(title="World map (robinson)") + 
  coord_equal() +
  theme_opts
 
ggsave("maps/map2.png", width=12.5, height=8.25, dpi=72)

Here the world map is shown using the Robinson projection. World map in ggplot with robinson projection 

# show hole
ggplot(wmap_df_robin, aes(long,lat, group=group, fill=hole)) +
  geom_polygon() + 
  labs(title="World map (robin)") +
  coord_equal() + 
  theme_opts
ggsave("maps/map3.png", width=12.5, height=8.25, dpi=72)

However, the Caspian sea is missing. This is because of how ggplot handles polygon holes. Ggplot will plot polygon holes as a separate polygon, thus we need to make it pseudo-transparent by changing its fill color.

![World map in ggplot2 polygon hole example][./img/map3.png]

# change colors
ggplot(wmap_df_robin, aes(long,lat, group=group, fill=hole)) + 
  geom_polygon() + 
  labs(title="World map (Robinson)") + 
  coord_equal() + 
  theme_opts +
  scale_fill_manual(values=c("#262626", "#e6e8ed"), guide="none") # change colors & remove legend
 
ggsave("maps/map4.png", width=12.5, height=8.25, dpi=72)

Now the Caspian sea is visible. World map in ggplot polygon hole fix 

# add graticule and bounding box (longlat)
grat <- readOGR("ne_110m_graticules_all", layer="ne_110m_graticules_15") 
grat_df <- fortify(grat)
 
bbox <- readOGR("ne_110m_graticules_all", layer="ne_110m_wgs84_bounding_box") 
bbox_df<- fortify(bbox)
 
ggplot(bbox_df, aes(long,lat, group=group)) + 
  geom_polygon(fill="white") +
  geom_polygon(data=wmap_df, aes(long,lat, group=group, fill=hole)) + 
  geom_path(data=grat_df, aes(long, lat, group=group, fill=NULL), linetype="dashed", color="grey50") +
  labs(title="World map + graticule (longlat)") + 
  coord_equal() + 
  theme_opts +
  scale_fill_manual(values=c("black", "white"), guide="none") # change colors & remove legend
 
ggsave("maps/map5.png", width=12.5, height=8.25, dpi=72)

If we want we can also add a graticule and a bounding box. The bounding box is useful if we want to make the sea blue—especially when using some form of curved projection. Here I have added a graticule and bounding box to the longlat-map.

World map in ggplot plus graticule and bounding box 

# graticule (Robin)
grat_robin <- spTransform(grat, CRS("+proj=robin"))  # reproject graticule
grat_df_robin <- fortify(grat_robin)
bbox_robin <- spTransform(bbox, CRS("+proj=robin"))  # reproject bounding box
bbox_robin_df <- fortify(bbox_robin)
 
ggplot(bbox_robin_df, aes(long,lat, group=group)) + 
  geom_polygon(fill="white") +
  geom_polygon(data=wmap_df_robin, aes(long,lat, group=group, fill=hole)) + 
  geom_path(data=grat_df_robin, aes(long, lat, group=group, fill=NULL), linetype="dashed", color="grey50") +
  labs(title="World map (Robinson)") + 
  coord_equal() + 
  theme_opts +
  scale_fill_manual(values=c("black", "white"), guide="none") # change colors & remove legend
 
ggsave("maps/map6.png", width=12.5, height=8.25, dpi=72)

Robinson projection with added graticule and bounding box. World map in ggplot using robinson projection with graticule and bounding box 

# add country borders
countries <- readOGR("ne_110m_admin_0_countries", layer="ne_110m_admin_0_countries") 
countries_robin <- spTransform(countries, CRS("+init=ESRI:54030"))
countries_robin_df <- fortify(countries_robin)
 
ggplot(bbox_robin_df, aes(long,lat, group=group)) + 
  geom_polygon(fill="white") +
  geom_polygon(data=countries_robin_df, aes(long,lat, group=group, fill=hole)) + 
  geom_path(data=countries_robin_df, aes(long,lat, group=group, fill=hole), color="white", size=0.3) +
  geom_path(data=grat_df_robin, aes(long, lat, group=group, fill=NULL), linetype="dashed", color="grey50") +
  labs(title="World map (Robinson)") + 
  coord_equal() + 
  theme_opts +
  scale_fill_manual(values=c("black", "white"), guide="none") # change colors & remove legend
 
ggsave("maps/map7.png", width=12.5, height=8.25, dpi=72)

Here I have added country borders to the previous map plot. World map in ggplot in robinson projection with country borders 

# bubble plot
places <- readOGR("ne_110m_populated_places", layer="ne_110m_populated_places") 
places_df <- as(places, "data.frame")
places_robin_df <- project(cbind(places_df$LONGITUDE, places_df$LATITUDE), proj="+init=ESRI:54030") 
places_robin_df <- as.data.frame(places_robin_df)
names(places_robin_df) <- c("LONGITUDE", "LATITUDE")
places_robin_df$POP2000 <- places_df$POP2000 
 
ggplot(bbox_robin_df, aes(long,lat, group=group)) + 
  geom_polygon(fill="white") +
  geom_polygon(data=countries_robin_df, aes(long,lat, group=group, fill=hole)) + 
  geom_point(data=places_robin_df, aes(LONGITUDE, LATITUDE, group=NULL, fill=NULL, size=POP2000), color="#32caf6", alpha=I(8/10)) +
  geom_path(data=countries_robin_df, aes(long,lat, group=group, fill=hole), color="white", size=0.3) +
  geom_path(data=grat_df_robin, aes(long, lat, group=group, fill=NULL), linetype="dashed", color="grey50") +
  labs(title="World map (Robinson)") + 
  coord_equal() + 
  theme_opts +
  scale_fill_manual(values=c("black", "white"), guide="none")+
  scale_size_continuous(range=c(1,20), guide="none")# change colors & remove legend
ggsave("maps/map8.png", width=12.5, height=8.25, dpi=72)

Bubble plots are a popular way of displaying information on maps. Here I used project() to reproject the bubbles’ coordinates into the Robinson projection. World map in ggplot using robinson projection plus bubble plot 

# Winkel tripel projection
countries_wintri <- spTransform(countries, CRS("+proj=wintri"))
bbox_wintri <- spTransform(bbox, CRS("+proj=wintri"))
wmap_wintri <- spTransform(wmap, CRS("+proj=wintri"))
grat_wintri <- spTransform(grat, CRS("+proj=wintri"))
 
p<-ggplot(bbox_wintri, aes(long,lat, group=group)) + 
  geom_polygon(fill="white") +
  geom_polygon(data=countries_wintri, aes(long,lat, group=group, fill=hole)) + 
  geom_path(data=countries_wintri, aes(long,lat, group=group, fill=hole), color="white", size=0.3) +
  geom_path(data=grat_wintri, aes(long, lat, group=group, fill=NULL), linetype="dashed", color="grey50") +
  labs(title="World map (Winkel Tripel)") + 
  coord_equal(ratio=1) + 
  theme_opts +
  scale_fill_manual(values=c("black", "white"), guide="none") # change colors & remove legend
 
ggsave(plot=p, "maps/map9.png", width=12.5, height=8.25, dpi=72)

Lastly, here is an example of the Winkel tripel projection. This projection became popular after 1998 when the National Geographic Society choose to use it for their world maps—using it to replace the Robinson projection, which they previously used.
World map in ggplot using winkel tripel projection

Kristoffer Magnusson

Written by Kristoffer Magnusson, a researcher in clinical psychology. You should follow him on Bluesky or on Twitter.

Share:
ggplot2ProjectionMapsrgdal

Published May 23, 2013 (View on GitHub)

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Really helpful visualisations, thanks!

Someone bought ☕ (1) coffee

This is amazing stuff. Very slick. 

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Sarko bought ☕ (1) coffee

Thanks so much for creating this! Really helpful for being able to explain effect size to a clinician I'm doing an analysis for. 

@DominikaSlus bought ☕ (1) coffee

Thank you! This page is super useful. I'll spread the word. 

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Melinda Rice bought ☕ (1) coffee

Thank you so much for creating these tools! As we face the challenge of teaching statistical concepts online, this is an invaluable resource.

@tmoldwin bought ☕ (1) coffee

Fantastic resource. I think you would be well served to have one page indexing all your visualizations, that would make it more accessible for sharing as a common resource.

Someone bought ☕ (1) coffee

Fantastic Visualizations! Amazing way to to demonstrate how n/power/beta/alpha/effect size are all interrelated - especially for visual learners! Thank you for creating this?

@jackferd bought ☕ (1) coffee

Incredible visualizations and the best power analysis software on R.

Cameron Proctor bought ☕ (1) coffee

Great website!

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Hanah Chapman bought ☕ (1) coffee

Thank you for this work!!

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Jayme bought ☕ (1) coffee

Nice explanation and visual guide of Cohen's d

Bart Comly Boyce bought ☕ (1) coffee

thank you

Dr. Mitchell Earleywine bought ☕ (1) coffee

This site is superb!

Florent bought ☕ (1) coffee

Zampeta bought ☕ (1) coffee

thank you for sharing your work. 

Mila bought ☕ (1) coffee

Thank you for the website, made me smile AND smarter :O enjoy your coffee! :)

Deb bought ☕ (1) coffee

Struggling with statistics and your interactive diagram made me smile to see that someone cares enough about us strugglers to make a visual to help us out!😍 

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@exerpsysing bought ☕ (1) coffee

Much thanks! Visualizations are key to my learning style! 

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Archived Comments (13)

H
Hedvig Skirgård 2018-12-14

Tack, det här är jättebra. Jag måste dock tweaka lite pga vill inte ha default centrering, så det blir lite krångliare. Jag har hellre en brytning i atlanten än i Stilla Havet, så dom flesta lösningar jag hittar för bra projektioner måste jag modda mer.. men.. jaja. Tack i alla fall ^^!

J
JPMD 2016-08-12

Great Tutorial. Thanks Kristoffer. I do have a problem with the projection when I get the map data from maps library:
map <- map_data("world")
map <- subset(map, region!="Antarctica")
map <- spTransform(map, CRS("+proj=wintri"))

Gives me this error:

Error in (function (classes, fdef, mtable) :
unable to find an inherited method for function ‘spTransform’ for signature ‘"data.frame", "CRS"’

Any clue of why this might be?
Thanks.

S
Sri Satya 2016-02-23

could you guys please help me out with my query.............I would like to create a calender using (R- studio) and i want to show the description pop-up on the date field when i moves my courser on a
specified date.

M
mielniczuk 2015-02-25

wanting to learn how to use shape files within R, tried replicating your tutorial. Using latest ver of required libraries and shape files. Now getting err: - Error in ogrInfo(dsn = dsn, layer = layer, encoding = encoding, use_iconv = use_iconv, : Cannot open file. Online references point to 'possible errs in topography'. I notice that your tutorial on R-bloggers now displays the map graphics as broken links. Any thoughts?

S
Sabrina 2014-02-19

I tried but didn't succeed (sorry, just started with R), how may I change the colours of the countries, e.g. fill the United States with blue and Japan with yellow? Is there an easy way to do that?

S
Sabrina 2014-02-19

I think readOGR/rgdal changed somehow (and I have the latest version), it only worked when I read it in as wmap <- readOGR(dsn="path to the folder which contains the shapefiles", layer="ne_110m_land").

Amazing tutorial!!

F
Friso Muijsers 2013-11-27

Short update: I managed to project my own data onto the map, however I failed in converting my long-lat data to robinson projection. Have to use the normal projection instead.

F
Friso Muijsers 2013-11-22

Hi, great post!! Is there a simple way to create a custom file with places instead of the one that you used. I have data from different places with long-and latt data, which I would love to project on that map.

Greetings

Friso

I
irakliloladze 2013-11-02

Thank you for the great and elegant post! Is there a simple way to add a specific latitude to the map? grat gives only a choice of major latitudes. What if I only want to draw a single latitude (and no longitudes) on the map?

M
Matt 2013-10-17

Thanks for this. Nice post. Pretty new to the idea of mapping in R, surprised that there were so few tutorials around on the web. I was working on pulling the country names in too so you could tag a lists of countries for coding appropriately etc. Will look to post that back here once I have it refined. Cheers

J
Jeremy 2013-08-24

This is great. Very easy to follow and expand upon. Actually, I was trying to grab the ocean shapefiles as well (I know it seems strange to overlay the ocean shapes onto the land shapefiles, but for I am doing it makes sense) and the website says that the "polygons are split into contiguous pieces." When I plot this downloaded files, it seems that it only shows the oceans around Asia and Africa. Not sure if that is supposed to be that way or I have something wrong. In the latter instance, using the routine described above does anyone know of a way to join these pieces together?

M
Michael MacAskill 2013-05-27

Nice post. I know the Robinson and Winkel projections work better overall, but being a Kiwi I prefer the old fashioned Mercator projection if only because the others tend to turn New Zealand into a disortorted smear at the edge of the world...

Kristoffer Magnusson 2013-05-27

Well, the Mercator projection will make Sweden look bigger than it is, so I'm not wholly against it. Luckily Sweden is close to the prime median, else it would probably look like New Zealand...