80 Data Visualization Examples Using Location Data and Maps

As the importance of location data continues to grow so do the ways you can visualize this information. We’ve scoured the web in search of data visualizations showing the value of location data in its many varieties, and have compiled this mega list to bring you the very best examples. The 80 entries below surprised us, taught us, inspired us, and drastically changed the way we understand location data.

We grouped these 80 data visualizations into thematic categories, and then listed each entry (click on the name of the visualization to open it). The six categories include:

From data visualizations on global breathing patterns, to fan reactions to the latest episode of Game of Thrones, to international diplomacy and humanitarian crises, these 80 data visualizations are only a small glimpse into the different ways location data is being used around the world.


Conflict Zones

World Migration Map
With open data on worldwide net migration between 2010 and 2015 provided by the United Nations Population Division, Max Galka set out to visualize this large volume of data in one map. The result? An incredible resource charting migration flow patterns from origin-to-destination spanning five years. In visualizing this location data, the “World Migration Map” provides a transparency tool that can help fact check politicians flaming fears with heated rhetoric about walls and what not. You can read Galka’s full analysis here.

Peter Aldhous’ “Spies in the Sky” data visualization reveals flight track patterns of the U. S. government’s airborne surveillance using aircraft location data provided by flightradar24. Individual aircraft flights are represented by animated dots while dense circles indicate regularly monitored areas. The data visualization color palette-red, white, and blue-reinforces Aldhous’s point, and perhaps explains why National Geographic ranked “Spies in the Sky” among its best maps of 2016.

Syria After Four Years of Mayhem
Before and after pictures can seem gimmicky, but Sergio Pecanha, Jeremy White, and K. K. Rebecca Lai reminded us of this genre’s effectiveness in “Syria After Four Years of Mayhem” (2015). Leveraging satellite imagery, location data from IHS Energy Data Information Navigator, and data from several humanitarian relief agencies, the authors show the devastation of the Syrian civil war by visualizing how in two years “the country is 83 percent darker at night than before the war.”

The Refugee Project
Hyperakt’s The Refugee Project reminds us that art is a medium for political protest. This data visualization is both a resource that uses United Nations’ refugee data to enable comparative studies on refugee migration and a work of art that New York’s Museum of Modern Art selected for its “Design and Violence” exhibit.

The Shape of Slavery
Michelle Alexander’sThe New Jim Crow, a major source for Ava DuVernay’s , identified Jim Crow legislation as the origins of the “school to prison pipeline.” In The Shape of Slavery, Bill Rankin and Matt Daniels distill the location component of historical data related to slavery and incarceration rates to provide visual proof that America, far from being a “post-racial” society, “is only recently a post- slavery one.”

White Collar Crime Risk Zones
The New Inquiry is bucking a data visualization trend that maps open data from police reports that tend to focus on “street crime” prevention. Instead, this data visualization uses machine learning to locate white collar crime risk zones (and provide some uncanny facial profiles!). Brian Clifton, Sam Lavigne, and Francis Tseng explain their methodology here, and we’re excited to enter this brave new world of data visualizatons!



Breathing Earth
John Nelson’s Breathing Earth used satellite images from NASA’s Visible Earth catalog to create an animated data visualization showing the earth’s pulse through a year’s seasonal transformation. The map was a huge hit, and has spawned many noteworthy follow-ups including Nadieh Bremer’s A Breathing Earth (2016) and an entry included a little further down on our list!

Cloudy Earth
We’ve looked at clouds from both sides, but NASA Earth Observatory has us beat with its visualization of cloud data between July 2002 and August 2015. Cloudy Earth attempts to visualize data on clouds, one of the least understood components of our climate, in order to study its role in global climate change. NASA’s Aqua satellite, and its MODIS sensor, provided imagery and location data for this visualization whose cool-blue color palette and time-lapse animation enables viewers to easily identify patches of high cloud density around the world.

Global Historical Emissions Map
Similar to the Smithsonian’s E3 data visualization, Aurélien Saussay’s Global Historical Emissions Map surveys environmental changes over time. However, this data visualization displays location data on fossil-fuel burning and gas flaring as well as cement production between 1750 and 2010. You can read more about Saussay’s methodological approach to mapping the industrial revolution’s historical impact as well as his decision to use a gridded dataset here.

The Earth Wind Map
In 2013, Cameron Beccario created The Earth Wind Map, a data visualization showing global weather conditions as forecasted by supercomputers with updates every three hours. The project was originally inspired by Hint.fm’s Wind Map, a data visualization of wind patterns that automatically updates based upon available weather data. The Earth Wind Map’s use of location data is nothing short of revolutionary, which you’ll discover by interacting with the data visualization. See what the same location data looks like using a stereographic projection! In the words of Florence and the Machine: “So big, so blue, so beautiful!”

Five Years of Drought
The widely-celebrated Five Years of Drought, John Nelson’s second appearance on our list, visualizes 285 weeks of drought data as reported by the United States Drought Monitor in a single view. Despite its static design, the results, as Nelson writes, was “a map that accidentally characterizes the movingness of droughts over five years by using opacity to represent motion.” A great example of the role perceptual color theory plays in spatial analysis and data visualizations, both static and interactive!

MIT’s Senseable City Lab’s Treepedia maps location data related to tree canopies for cities around the world including Paris, Frankfurt, and Cape Town. Instead of mapping each individual tree in each city, these data visualizations are built with an analysis method that uses location data to show the “amount of green perceived while walking down the street.”

Sites, Sounds, and Smells of City Living

Fans on the Move
Are you willing to travel internationally to attend your favorite band’s concert? Your favorite sports team’s big game? Ticketbis, an international subsidiary of StubHub, examined 36 months of location data on attendees purchasing international tickets through its service, and the results are interesting. Spoiler: the Superbowl and 2012 Summer Olympics rank pretty high, but check out which countries of origin are home to some of the world’s most diehard groupies!

Mapping the Shadows of New York City: Every Building, Every Block
Manhattanhenge is great, but for the rest of the year New Yorkers take access to sunlight very, very seriously. In “The Struggle for Light and Air in America’s Largest City” (2016), Quoctrung Bui and Jeremy White built a data visualization of New York City that maps building shadows. Using location data on Manhattan buildings, Bui and White used ray tracing to simulate the effect of sunlight on each building and its surrounding area. The results are stunning as “dark” neighborhoods in the shadows of nearby skyscrapers are easily spotted. Location data can cast a long shadow it turns out!

The World Data Lab’s Population.io may be both the most comprehensive and informative visualization of location data on our list. One of our favorite interactive features is the visualization of demographic data based upon a map viewer’s date of birth, a neat way to show how in your own life span the world’s population has increased. Another interesting feature is the interactive map that estimates the remainder of your life expectancy based upon current location that can be compared to other countries around the world.

The Geographic Divide of Oscar Films
Inspired by Josh Katz’s cultural divide maps, Matt Daniels, Ilia Blinderman, and Russell Goldenberg over at The Pudding decided to see if cultural and geographical divides corresponded in relation to 2017 Oscar-nominated films. The maps are gorgeous, the methodology rigorous, and the widespread popularity of Arrival undeniable!

Locals & Tourists
We were impressed with the previous entry’s visualization of 3.3 million data points, but a year later Eric Fischer mapped 3 billion tweets in Locals & Tourists. This data visualization breaks down the tourist-local divide by mapping social data provided by GNIP. Learn more about what went into processing this high volume of geospatial data here.

Wikipedia Recent Changes Map
Stephen LaPorte and Mahmoud Hashemi’s data visualization tracks global updates to Wikipedia made by unregistered users. Although this population only amounts for approximately 15 percent of total Wikipedia updates, it is pretty cool to see how LaPorte and Hashemi used IP addresses to extract the geograhical location of unregistered users.


A Tale of Twenty-Two Million CitiBikes
In his almost Dickensian break down of location data extracted by CitiBike riders, Todd Schneider details the hidden story behind 22.2 million Citi Bike rides across New York City. We love the time-lapse animation tracking the route of each and every bike in use over the course of a day. Make sure to check out what rush hour looks like for bikers starting around 5:30pm for a whole new take on “it was the best of times, it was the worst of times.”

Kiln created this data visualization for The Guardian using data provided by FlightStats. This data visualization tracks individual flights in near real-time as well as flight routes identifying areas with high traffic volume each and every day. Watch the video before exploring the map for yourself!

Benedikt Groß, Philipp Schmitt, and Raphael Reimann over at Moovel Lab set out to determine whether all roads do, in fact, lead to Rome. Similar to other entries on our list, New Europe undertook a route optimizaton, but on a whole new level as they determined which of the nearly 500,000 roads leading to Rome was the best option. These data visualizations definitely weren’t built in a day, but we’re grateful for all the time and energy that went into mapping the routes from each of the 486,713 starting points! Learn more about the project here.

The Megaregions of the U.S.
Based upon their research related to economic geography across the United States, Garrett Dash Nelson and Alasdair Rae visualized this work in The Megaregions of the U.S. This data visualization participates in growing efforts to map beyond static boundaries and instead see what the U.S. “might look like if we based our regions on the pattern which commuters weave every day between cities, suburbs, and rural areas.” With more than four million lines, this data visualization weaves together beautiful digital cartography and innovative spatial analysis. A must see!

We hope you found these data visualizations as beautiful as we did. Let us know about any projects we missed on Twitter, Facebook, and LinkedIn!


Article by channel:

Read more articles tagged: Data Visualisation