Joy Division, Population Surfaces and Pioneering Electronic Cartography

July 28, 2017
By

(This article was first published on R – Spatial.ly, and kindly contributed to R-bloggers)

There has been a resurgence of interest in data visualizations inspired by Joy Division’s Unknown Pleasures album cover. These so-called “Joy Plots” are easier to create thanks to the development of the “ggjoy” R package and also some nice code posted using D3. I produced a global population map (details here) using a similar technique in 2013 and since then I’ve been on a quest to find some earlier examples. This is because a number of people have said it reminds them of maps created by Harvard’s digital mapping pioneers in the 1970s and I got the feeling I was coming late to the party…

The pulsar style plots are already well covered by Jen Christiansen who wrote an excellent blog post about the Joy Division album cover, which includes many examples in a range of scientific publications and also features this interview with the designer Peter Saville.

Most interestingly, Jen’s post also includes the glimpse of the kind of map (top left) that I’d heard about but have been unable to get my hands on shown in the book Graphis Diagrams: The Graphic Visualization of Abstract Data.

My luck changed this week thanks to a kind email from John Hessler (Specialist in Mathematical Cartography and GIS at the Library of Congress) alerting me to the huge archive of work they have associated with GIS pioneer Roger Tomlinson (who’s PhD thesis I feature here). I enquired if he knew anything about the population lines maps to which he causally replied “we have hundreds of those” and that he’d already been blogging extensively on the early GIS/ spatial analysis pioneers (I’ve posted links below).

John sent me the below movie entitled “American Graph Fleeting, United States Population Growth 1790-1970” created in 1978. It’s extraordinary, both in how contemporary it looks but also because it was created as a hologram!

 

He writes:

In 1978 Geoffrey Dutton, who was at the Harvard Lab for Computer Graphics and Spatial Analysis, decided to make a spatial-temporal holographic projection based on the work of William Warntz (see my article How to Map a Sandwich: Surface, Topological Existence Theorems and the Changing Nature of Thematic Cartography for an image of the original Warntz population surface). Dutton’s surface projections were made from the ASPEX software with population data smoothed on to grid of 82 x 127 cells ( a lot to handle computationally at the time)…

The first two images below show the hologram in action and the third shows how it was created.

If you want to find out more information and this pioneering work (and remind yourself how far we have/haven’t come), John Hessler’s “Computing Space” series of blog posts are a great place to start:

From Hypersurfaces to Algorithms: Saving Early Computer Cartography at the Library of Congress
Ernesto and Kathy Split a Sandwich
Taking Waldo Tobler’s Geography 482
Papers of the “Father of GIS” Come to the Library of Congress
Computing Space IV: William Bunge and The Philosophy of Maps
The Many Languages of Space or How to Read Marble and Dacey
Mapping the Web or Pinging your Way to Infinity
Searching for Magpie and Possum: Contemplating the Algorithmic Nature of Cartographic Space
Games Cartographers Play: Alphago, Neural Networks and Tobler’s First Law

To leave a comment for the author, please follow the link and comment on their blog: R – Spatial.ly.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)