Julien Gaffuri’s map of the second-round results of the French presidential election is, as you can see, extraordinarily busy—and, by the way, extremely processor-intensive: it will slow down your machine—because it’s at the commune level and each circle is scaled to population. (News flash: Paris has lots of people in it.) And those circles are striped circles: the proportion of the votes is indicated by the area taken up by a given colour. The map of the first round results shows more stripes (because more candidates) but is by department, so it’s a little easier both to read and to see how the striped circle format works. It’s an interesting alternative to a choropleth map, and a bit less ambiguous.

Atlas of the Invisible

The Royal Geographic Society reprints a map from the book showing the flow of ice on the Greenland ice cap and interviews James about how they used the data. James has also published some education resources related to the book on his website. And of course there’s more at the book’s website.

See John Grimwade’s post about the book, in which he asks the authors about their ideas and process. Also see reviews from Fast Company and the Guardian.

Amazon (Canada, UK) | Bookshop

Previously: Where the Animals Go.

Related: Map Books of 2021.

Kenneth Field’s long-awaited Thematic Mapping: 101 Ways to Visualise Empirical Data, which takes as its starting point a map of a single event—the 2016 U.S. presidential election—will be out from Esri Press as an ebook on the 31st of August, Ken announced yesterday. Pre-order: Amazon (Canada, UK).

You might remember James Cheshire and Oliver Uberti’s amazing 2016 book Where the Animals Go. Their next book of data visualizations, Atlas of the Invisible, will be out in September from Particular Books in the U.K. and in November from W. W. Norton in North America. Pre-order: Amazon (Canada, UK), Bookshop.

The Quarantine Atlas: Mapping Life under COVID-19 is the byproduct of CityLab’s 2020 project soliciting hand-drawn maps of life under quarantine (previously here and here). In the book version, Laura Bliss matches 65 of those submissions with original essays. Due out in April 2022 from Black Dog & Leventhal. Pre-order: Amazon (Canada).

I’ve updated the Map Books of 2021 page with these books; that page still looks awfully sparse compared with previous years. If there’s a map-related book coming out this year that I haven’t listed, please let me know.

Erin Davis has created maps showing the average colour of each country of the world (plus  maps showing the average colour of each U.S. state and county). She derived the average colour from Sentinel-2 natural-colour satellite imagery; she appends the process and the code to the end of her post. [My Modern Met]

Kai’s Comparing Map Projections mashes up two code blocks by Mike Bostock: Map Projections Distortions is a visualization of the types of distortion inherent to each projection; Projection Transitions morphs between projections. Combining the two is a neat trick. Refreshing to see the usual two combatants excluded. [Maps Mania]

Data.Pour.Paris is a collection of interactive maps about the city of Paris. It’s a lot more interesting—and granular—than it appears at first glance, though. The traffic and real-time metro maps you might expect, but the map of street lights drills down to individual streetlights—and their wattage. Public order complaints are mapped individually, and there’s even a map of the 2018 Paris marathon that tracks the progress of individual runners. They’re the work of French engineer Benjamin Tran Dinh, and they’re neat. They speak as much to the availability of such data as the ability to map it. [Maps Mania]

Previously: Le Grand Paris en Cartes.

Update: The above is lacking in some detail; here’s the Toronto Star review to make up for it.

She followed that up with another post focusing on one particular factor: the size of the geographic unit. Choropleth maps that shows data by municipality, county, region, state or country will look quite different, even if they show the same data. Averages tend to cancel out extremes. She gives the following examples:

Datawrapper has added population cartograms to its map collections, and in its blog post discusses the advantages and disadvantages of cartograms vs. geographical maps, as well as the advantages and disadvantages of some of the different types of cartograms. Turns out that cartograms are kind of like map projections: each has its pros and cons; each is better suited to some uses than to others. [Caitlin Dempsey]

A data visualization by Gwilym Lockwood looks at where passengers get on and off the tube—it’s “a geographically accurate map of the London tube lines, sized by number of passengers getting on and off at each station.” Hovering over and clicking on each station reveals more data. [Maps Mania]

Here’s something neat from Garrett Dash Nelson: “the total seasonal snowfall in the continental US for 2017–2018 so far, shown as a relief map,” where total snowfall is expressed as elevation. That’s neat. Even neater: the animated gif that depicts it (a frame of which is above). Even neater than that: he shows how he made said animated gif.

Here’s an animated map showing each country’s average life expectancy at birth for every year since 1960, posted by Reddit user DataFreelancer to the Data Is Beautiful subreddit. [Boing Boing]

There are many types of maps that are used to display data. Choropleths and Cartograms provide two great examples. I gave a talk, long long ago, about some of these map varieties.

Most of these more common map types focus on a particular variable that is displayed. But what if you have multiple variables that you would like to present on a map at the same time?

Here is my attempt to collect examples of multivariate maps I’ve found and organize them into a loose categorization. Follow along, or dive into the references, to spur on your own investigations and inspirations!

Jim’s examples of maps that display more than one variable include 3D maps, multicolour choropleth maps, multiple small maps, and embedded charts and symbols. Useful and enlightening.

Ingo Günther’s World Processor project, which projects historical, political, social and environmental data visualizations onto literally hundreds of illuminated globes, gets a writeup in, of all places, Bloomberg’s Pursuits section, which treats his globes as a luxury good: “as much fine-art object as C-suite accoutrement.” This seems rather beside Günther’s point, in spectacularly late-capitalist fashion. [The Map as Art]

I first told you about Günther’s work in 2005. Here’s his home page, and an exhibit at the Bryce Wolkowitz Gallery.

Will Geary’s TransitFlow project is an experimental set of tools to build animated transit flow visualizations, built from Transitland’s open-source transit schedule data. More than a dozen visualizations are available in video form here; each shows the flow of trains, buses and other forms of transport over the course of a day. Very high visual appeal. More at the Guardian. [Metrocosm]

Previously: Live Marine Traffic Maps; ESA Maps European Shipping Routes.

Dissatisfied with the maps of the EU referendum results he encontered, Bob Taylor crunched the numbers and produced some interesting maps of his own, including choropleth maps, cartograms, and maps identifying clusters of support for leave and remain. [Yanko Tsvetkov]

Sajjad Anwar and Sanjay Bhangar have been playing with train, station and schedule data from Indian Railways, one result of which (so far) is this reachability map—all the destinations reachable by a single train (i.e., without a transfer) from a given station. [Sajjad Anwar]

Previously: A Map of India’s Railway Network.

The Ordnance Survey has created a series of data visualizations showing the most popular walking and cycling routes, based on OS Maps usage. “The 500,000 plus routes were illustrated in a series of beautiful data visualisations by [cartographic designer] Charley [Glynn], who found it amazing that the people who created routes for their outdoors adventures had logged almost every bit of British coastline. It neatly frames the rest of the data and gives the illusion you are looking at a map of Great Britain. The darker, thicker areas illustrate the higher concentration of routes and reveal popularity.” Flickr gallery. [Mountain Bike Rider]

It's been a while since I've published a map so here's 2015 house prices by postcode across Britain pic.twitter.com/p5AexvYokS

— Neal Hudson (@resi_analyst) April 14, 2016

[Maps on the Web]

(Worth mentioning that this is exactly the sort of thing dealt with in Mark Monmonier’s How to Lie with Maps.)

BatiParis is an online map that shows the age of buildings in Paris (most of which, it reveals, were built between 1851 and 1914.) A note on the interface: clicking on the legend toggles the period of construction, so clicking on a date range removes it from the map the first time. [via]

Project Ukko visualizes seasonal wind predictions, i.e., the amount of wind that is forecasted for the upcoming season. It’s the sort of thing the wind generation industry would find useful. But such a prosaic purpose is belied by the breathtaking way in which the data is visualized. [via]

Le Grand Paris en Cartes is a collection of interactive maps and infographics about the Grand Paris Express, a multi-billion-euro project to extend Paris’s Metro and rapid transit network deep into the surrounding Île-de-France region (if you can read French, the official site and French Wikipedia page provide a lot more information). These maps not only illustrate Parisians’ commuting routes and Metro usage, but also (see above) the kind of sociological data that underpins transit planning: employment centres, population density and so forth. In French. [via]

An online map of Japanese municipalities that uses census data to measure their relative economic health. [via]

Here are two interactive maps that show the scale of recent refugee migrations. Lucify’s interactive map (screenshot above) shows the flow of asylum seekers to European countries since 2012. And this interactive map, compiled by The Conversation from UNHCR data, shows the size of refugee populations originating from or residing within each country from 1975 to 2010. In each case, the numbers grow with each passing year. More from Scientific American’s SA Visual blog. [via]