Earthquakes are in the news a lot lately. A quick search shows a 7.6 off the coast of the Solomon Islands, a 6.6 in Nicaragua, and a 7.1 off the southwest coast of Papua New Guinea, and this was just last week. Not good news at all, but just how common are these earthquakes? Can we look back farther? Yes. In addition to a real-time feed of earthquakes, the United States Geological Survey maintains an ever growing archive of earthquakes detected around the world, and they make it easy to query and download.
The map above shows the past century of known earthquakes with a magnitude of at least 5. (There are actually nearly a million earthquakes per year, but most of them are not felt. A earthquake of magnitude 5 might cause damage to buildings.) Each white dot is a quake, of which there were about 72,000, and as you’d expect, you get a sense of plates tectonic boundaries.
The ten earthquakes of highest magnitude in the past 100 years are highlighted green.
Make the map
Because the data is already there, it’s trivial to map in R. Just (1) download CSV data from USGS; (2) use
map() from the maps package to draw a base map; and (3) project points with
mapproject() and add them to the map.
library(maps) library(mapproj) # Load data quakes <- read.csv('http://datasets.flowingdata.com/earthquakes1974.csv') # Draw map par(mar=c(0,0,0,0)) map("world", col="orange", bg="#000000", fill=FALSE, interior=TRUE, lwd=0.5, projection="cylequalarea", par=0, wrap=TRUE) # Add points ptsproj <- mapproject(quakes$longitude, quakes$latitude) points(ptsproj, pch=20, cex=0.15, col="#ffffff40") # Circle the highest magnitude quakes quakes.o <- quakes[order(quakes$mag, decreasing=TRUE),] majorpts <- mapproject(quakes.o$longitude[1:10], quakes.o$latitude[1:10]) symbols(majorpts, circles=rep(0.03, 10), add=TRUE, inches=FALSE, fg="green", lwd=2)
Note that the dataset linked in the code is just a small sample of what’s available.
Of course, there’s much more to look at here than just an aggregate map. In addition to latitude and longitude, the data includes time, depth, magnitude, and more specifics about location. USGS also goes back farther than a century. Hopefully this helps you get started.
Become a member. Learn to visualize data. From beginner to advanced.Join Today
This is for people interested in the process of creating, designing, and exploring data graphics. Your support goes directly to FlowingData, an independently run site.
What You Get
- Instant access to tutorials on how to make and design data graphics
- Source code and files to use with your own data
- In-depth courses on visualization in R
- Hand-picked links and resources from around the web
- Members-only newsletter
Visualizing the Uncertainty in Data
Data is an abstraction, and it’s impossible to encapsulate everything it represents in real life. So there is uncertainty. Here are ways to visualize the uncertainty.
One Dataset, Visualized 25 Ways
“Let the data speak” they say. But what happens when the data rambles on and on?