The most interesting question to consider is not the structure of the networks represented by air travel and internet activity. The nodes of both air travel and internet traffic line up exactly with the cities and metropolitan areas represented in the population map, and they align well with the concentration of lighted areas in the bottom frame as well. The patterns of both air travel and internet traffic take the form of a swath extending from the dense eastern corridor of the US (Boston to Washington) to California (San Francisco to San Diego), with Chicago standing out as a significant node in the middle of the country. This is entirely obvious and predictable; travel and communication follow population density.
Rather, the more interesting question is this: to what extent is there evidence of internet and air traffic at a node that is disproportionately greater than would be expected given the population of that node? This is the kind of question that drives Saskia Sassen’s classification of cities as local, regional, national, and global (The Global City: New York, London, Tokyo and Global Networks, Linked Cities). (Here is an earlier post on Sassen’s work.)
Fundamentally, a city that originates 10 times the volume of internet traffic compared to other cities of similar size is worth looking at in detail. Its activity level suggest an exceptional concentration of organizations and people that are unusually integrated into global networks of communication and data exchange. It is a location for knowledge-intensive activity: high-end services, banking, universities; and it is a place with intensive relations to other nodes. Likewise, a city that originates 5 times as many air-travel passengers as comparably sized cities elsewhere is likely to be a specialized location for business and high-end service activity (or else a population of very dedicated tourists). In other words, the most interesting feature that these data sets might show us about the economic roles of US cities is not visible in the graphics presented here.
Likewise, it would be interesting to identify the cities that have lower-than-expected levels of travel or internet activity; this would suggest local economies that are somewhat more self-contained and less integrated into the national economy than other locations. And it would be interesting to see if there are significant pairings among locations for either kind of transaction; for example, is the volume of data exchange between Los Angeles and New York significantly greater than that between New York and Chicago or Boston? And would this serve as an indicator of the degree of economic and business integration between these specific locations?
These views of the United States are interesting because they allow us to see the country as an inter-connected system of places and activities. They serve as something like a dynamic CT scan of the brain: certain connections between places “light up”, providing an indication of systemic activities that warrant further investigation.