Profiling the Complexity
of American Cities.

A while ago, the Lab did a project on the urban complexity craze in the 80's and 90's. There was a lot of talk then about "the urban issue," and entire cities were written off as problems that were too complex to solve.

Detroit was written off as a problem that was too complex to solve.

And so, like any hypothesis, we tested it rigorously. Are cities complex objects? And, if so, then what is the metric of urban complexity? What does it mean to measure the complexity of any network?

This led us to IQ: a local complexity measure for network-structured data. Not just for urban road networks, or urban networks at all, but graphs as mathematical objects.

It's a practical implementation not just of statistics, but information theory. And it has surprisingly strong connections to Deep Learning. Check out our Field Notes for more.

Beta-Release Access is restricted to Collaborators.