Daniel Huffman had the opportunity to redesign an airline’s route map for their in-flight magazine. He came up with the above design, which in the end the client decided against, but he talks about how he came up with it in this blog post. He calls it a cartogram, because he’s expanding or shrinking the continents to account for where the routes are clustered (which I guess kind of counts); and he’s adopted what he calls a “root-and-branch” style to avoid the cluttering and overlapping of multiple lines. It’s a fascinating read, particularly if you like learning about the mapmaking process.
Transit map designer Jug Cerović has reposted a look at the state of the art of European bus network maps. “I have studied more than 250 European cities and their bus maps, and have also designed a few. Here are some observations about the state of the practice.” He groups bus maps into three categories, based on how they use colour: maps that use colour to show the technology used (bus, metro, subway); maps that use colour to indicate individual lines; and maps that use colour and width to show bus frequency. Now Jug shows examples of each, and goes through the pros and cons, but he does have some skin in this game: he’s a fan of frequency maps, which he suggests solves the problems of the other two kinds, and in fact has produced frequency maps for Luxembourg (above) and Utrecht. Definitely worth a read if you’re interested in transit map design.
Scientific American reprints a 2016 article from The Mathematical Intelligencer on an obscure, but important, corner of transit map design: how to choose a colour for a metro line. The discussion is rather math heavy (and therefore above my pay grade), but the gist is that for ease of use lines’ colours should look as different from one another as possible, and it gets more complicated as you add more lines. “Not only must the new colors be unlike the old ones, but also they must differ from each other as much as possible.” The article discusses the math involved in choosing new colours. [WMS]
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.
The Art of Cartographics (Goodman) is available now in the U.K. but won’t come out in North America until March 2018. The publisher describes it as “a stunning collection of maps designed in a unique way. […] This carefully curated book selects the most creative and interesting map design projects from around the world, and offers inspiration for designers and map-lovers alike. Covering themes including power, gentrification, literature, animals, plants and food, and showcasing handrawn, painted, digital, 3D sculpted and folded maps, Cartographics offers a slice of social history that is as beautiful as it is fascinating.” Buy at Amazon U.K. | Pre-order at Amazon
Also out next week: the National Geographic Atlas of Beer (National Geographic). I have no information about the quantity or quality of the maps therein, but according to the publisher the book does have some: “The most visually stunning and comprehensive beer atlas available, this richly illustrated book includes more beers and more countries than any other book of its kind. Including beer recommendations from Garrett Oliver, the famed brewmaster of Brooklyn Brewery, and written by ‘beer geographers’ Nancy Hoalst-Pullen and Mark Patterson, this indispensable guide features more than 100 illuminating maps and over 200 beautiful color photos.” Buy at Amazon
The white underlying geographic map places states in their familiar size, shape and location, allowing them to be identified quickly. Using a cluster of dots rather than a solid fill to represent the outcome ensures that the amount of red and blue on the map accurately reflects states’ weight in the election outcome, rather than the (irrelevant) surface area.
Like the tiled grid cartogram, the number of electoral votes in each state is easy to compare visually without counting or interpreting numbers printed on the map. Because each electoral vote is a discrete mark, it is possible to accurately represent the split electoral votes that are possible in Maine and Nebraska, or the possibility of a faithless elector.