* UPDATED 2nd SEPTEMBER 2013 *

Whenever I have needed a map in a presentation, I have always slipped in a cheeky screenshot from Google and prayed that the copyright police won’t burst into the door and arrest me (talks are stressful enough). However, I was determined to change this, and after extensive trawling of the web, I’ve put together a quick template to make a simple large scale map for talks, presentations and posters using GIS shape files and ggplot2.

Here is the finished object (full code at the end of this page):

I started by downloading this excellent world map template from thematicmapping, and loading it into R using the maptools package:

library(maptools) 
gpclibPermit() 
## [1] TRUE 
worldmap <- readShapeSpatial("world_borders.shp") 

*** NB: You will require the library gpclib to read in the shapefile – if gpclibPermit() returns FALSE, then try installing gpclib again. As of Sep 2013, gpclib was not working in R v3.0.1. Argh. ***

The fortify function in ggplot2 will convert this to a data frame:

library(ggplot2)
worldmap <- fortify(worldmap) 
## Using CAT to define regions. 

Let’s have a quick look:

head(worldmap) 
## long lat order hole piece group id 
## 1 -69.88 12.41 1 FALSE 1 1.1 1 
## 2 -69.95 12.44 2 FALSE 1 1.1 1 
## 3 -70.06 12.53 3 FALSE 1 1.1 1 
## 4 -70.06 12.54 4 FALSE 1 1.1 1 
## 5 -70.06 12.54 5 FALSE 1 1.1 1 
## 6 -70.06 12.62 6 FALSE 1 1.1 1 

Essentially, this data frame is a list of paths/polygons (each one is part of a unique ‘group’) that we can plot using geom_path and geom_polygon. There are more than 400,000 points in this map which makes plotting quite slow, so I created a smaller data frame, worldmap2, to create rough maps for initial tweaking and formatting.

worldmap2 <- worldmap[seq(1, nrow(worldmap), 200), ] 

A quick plot using geom_polygon, creating groups based on the variable ‘group’:

ggplot(worldmap2, aes(x = long, y = lat, group = group)) + 
  geom_polygon() 

The same with geom_path:

ggplot(worldmap2, aes(x = long, y = lat, group = group)) + 
  geom_path() 

And using both (Put geom_path second in order to plot the borders):

ggplot(worldmap2, aes(x = long, y = lat, group = group)) + 
  geom_polygon() + 
  geom_path() 

Changing the colour of the polygons and path is straightforward:

ggplot(worldmap2, aes(x = long, y = lat, group = group)) + 
  geom_polygon(fill = "darkseagreen") + 
  geom_path(colour = "grey40") 

Creating a blue blackground required delving further into the mysterious world of theme(). I also changed the colour of the plot border and major grid lines to reduce the contrast slightly:

ggplot(worldmap2, aes(x = long, y = lat, group = group)) + 
  geom_polygon(fill = "darkseagreen") + 
  geom_path(colour = "grey40") + 
  theme(panel.background = element_rect(fill = "lightsteelblue2", colour = "grey"),
       panel.grid.major = element_line(colour = "grey90")) 

I wanted a map of Northern Europe, so I defined my latitude and longitude limits, and used coord_cartesian to zoom in onto the graph. With this mapfile, you can change latlimits and loglimits to your specific region of interest:

latlimits <- c(40, 75) 
longlimits <- c(-25, 50) 

ggplot(worldmap2, aes(x = long, y = lat, group = group)) + 
  geom_polygon(fill = "darkseagreen") + 
  geom_path(colour = "grey40") +
  theme(panel.background = element_rect(fill = "lightsteelblue2", colour = "grey"), 
       panel.grid.major = element_line(colour = "grey90")) +
  coord_cartesian(xlim = longlimits, ylim = latlimits) 

The scales are still more suited to the full graph, so now we can define our scale to be more relevant.

ggplot(worldmap2, aes(x = long, y = lat, group = group)) + 
  geom_polygon(fill = "darkseagreen") + 
  geom_path(colour = "grey40") +
  theme(panel.background = element_rect(fill = "lightsteelblue2", colour = "grey"), 
       panel.grid.major = element_line(colour = "grey90")) + 
  scale_y_continuous(breaks = seq(40, 70, 10)) + 
  scale_x_continuous(breaks = seq(-20, 40, 20)) +
  coord_cartesian(xlim = longlimits, ylim = latlimits) 

Now time to customise the graph a little more: removing the axis titles, relabelling the axes, removing the axis ticks, and making the text larger. Then we can use the original worldmap data frame to produce the final product:

# Final code:

library(maptools)
require(gpclib)
gpclibPermit()
worldmap <- readShapeSpatial("world_borders.shp")

library(ggplot2)
worldmap <- fortify(worldmap)

latlimits <- c(40, 75) 
longlimits <- c(-25, 50) 

ggplot(worldmap, aes(x = long, y = lat, group = group)) + 
  geom_polygon(fill = "darkseagreen") + 
  geom_path(colour = "grey40") + 
  theme(panel.background = element_rect(fill = "lightsteelblue2", colour = "grey"), 
       panel.grid.major = element_line(colour = "grey90"),
       panel.grid.minor = element_blank(),
       axis.ticks = element_blank(), 
       axis.text.x = element_text (size = 14, vjust = 0), 
       axis.text.y = element_text (size = 14, hjust = 1.3)) + 
  coord_cartesian(xlim = longlimits, ylim = latlimits) + 
  scale_y_continuous(breaks=seq(40,70,10), labels = c("40ºN", "50ºN", "60ºN", "70ºN")) + 
  scale_x_continuous(breaks=seq(-20,40,20), labels = c("20ºW", "0º" ,"20ºE", "40ºE")) + 
  labs(y="",x="")