After completing this tutorial, you will be able to:
- Create a quick basemap using
- Create a quick basemap using the
What you need
RStudio to complete this tutorial. Also you should have an
earth-analytics directory set up on your computer with a
/data directory with it.
# install devtools #install.packages("devtools") # install ggmap from dev space # devtools::install_github("dkahle/ggmap") library(ggmap)
First, create a basemap that shows the location of the stream gage in Boulder, Colorado.
myMap <- get_map(location = "Boulder, Colorado", source = "google", maptype = "terrain", crop = FALSE, zoom = 6) # plot map ggmap(myMap)
You can customize the base maps too - let’s change the
myMap <- get_map(location = "Boulder, Colorado", source="google", maptype="satellite", crop=FALSE, zoom=6) # plot map ggmap(myMap)
There are many other basemap options. Check out the help for
get_map by typing
??get_map into the
Let’s check out the stamen watercolor maps. Notice that I zoomed out some here so you can see the full effect of the new basemap.
myMap <- get_map(location = "Boulder, Colorado", source="stamen", maptype="watercolor", crop=FALSE, zoom=4) # plot map ggmap(myMap)
Ok, enough of the map play time - let’s get back to business. Next, let’s add a point to our map representing the location of our actual stream gage data.
Latitude: 40.051667 Longitude: 105.178333
USGS gage 06730200 40°03’06” 105°10’42”
# add points to your map # creating a sample data.frame with your lat/lon points gage_location <- data.frame(lon = c(-105.178333), lat = c(40.051667)) # create a map with a point location for boulder. ggmap(myMap) + labs(x = "", y = "") + geom_point(data = gage_location, aes(x = lon, y = lat, fill = "red", alpha = 0.2), size = 5, shape = 19) + guides(fill=FALSE, alpha=FALSE, size=FALSE)
Alternative - maps package
If you can’t install
ggmap, you can also create nice basemaps using the
maps package. The
maps package allows you to quickly create basemaps of study areas. It utilizes a set of vector based layers including layers that map:
- countries across the globe
- the United States and associated counties
- and more
You can use the
maps package, combined with the
base plot functions to add base layers to your map.
#install.packages('maps') library(maps) library(mapdata)
Create a basic map of the United States
map('state') # add a title to your map title('Map of the United States')
Plot using basemap - customize colors.
map('state', col = "darkgray", fill=TRUE, border="white") # add a title to your map title('Map of the United States')
Create a map of Colorado with county boundaries.
map('county', regions = "Colorado", col = "darkgray", fill = TRUE, border = "grey80") map('state', regions = "Colorado", col = "black", add = T) # add the x, y location of the stream guage using the points # notice i used two colors adn sized to may the symbol look a little brighter points(x = -105.178333, y = 40.051667, pch = 21, col = "violetred4", cex = 2) points(x = -105.178333, y = 40.051667, pch = 8, col = "white", cex = 1.3) # add a title to your map title('County Map of Colorado\nStream gage location')
You can stack several map layers using
add=TRUE. Notice you can create multi-line titles using
map('state', fill = TRUE, col = "darkgray", border = "white", lwd = 1) map(database = "usa", lwd = 1, add = T) # add the adjacent parts of the US; can't forget my homeland map("state", "colorado", col = "springgreen", lwd = 1, fill = TRUE, add = TRUE) # add gage location title("Stream gage location\nBoulder, Colorado") # add the x, y location of hte stream guage using the points points(x = -105.178333, y = 40.051667, pch = 8, col = "red", cex = 1.3)
Or you can plot with
usa <- map_data("usa") head(usa) ## long lat group order region subregion ## 1 -101.4 29.74 1 1 main <NA> ## 2 -101.4 29.74 1 2 main <NA> ## 3 -101.4 29.65 1 3 main <NA> ## 4 -101.4 29.64 1 4 main <NA> ## 5 -101.3 29.63 1 5 main <NA> ## 6 -101.3 29.64 1 6 main <NA>
ggplot() + geom_polygon(data = usa, aes(x = long, y = lat, group = group)) + coord_fixed(1.3)