Josh Begley

Fascinating patterns from overhead images of American military installations.

We first came across Josh Begley's clever approach at comprehending vast but often inaccessible infrastructure in 2012, when as an NYU graduate student he built a breathtaking database of aerial images of every correctional facility in the United States. That web project was an attempt to quantify the impact of incarceration on the American landscape, and the resulting visual was in many ways more powerful than any set of statistics showing the rise of the U.S. prison population or the proliferation of cell blocks needed to house it.

More recently, Begley has now applied the same idea to another difficult-to-measure subject: the American military's footprint. This website – empire.is – draws on Bing and Google Maps satellite images of the military installations identified in media reports and the Department of Defense's property inventory. Unlike the previous project, this geography extends well beyond the U.S. And it reveals more varied aerial patterns, from crisscrossing runways:

...to planned base housing communities:


... to, well, this, at Naval Communication Station Holt in Australia:

In one other way, the task of visualizing any military presence is harder than doing the same with our prisons. Some of these images are obscured or redacted, in curious ways:

Those tiles interspersed throughout the project raise questions as much about what we can't see as what we can. As Begley writes:

Beyond just adjudicating the differences between publicly-available satellite images, I wanted to start this project to think more broadly about mappable space. In the age of APIs, how might we see secrecy in aggregate? What would an aerial display of NSA data centers look like?

We've thought before about what the spread of data centers might look like from the sidewalk. But this is an entirely different way of trying to grasp the impact of institutional infrastructure (with varying implications), from 30,000 feet.

Hat tip: Flowing Data.

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