One of my summer projects this year has been attempting to map the American commute, following earlier work on a similar subject. Put simply, I've attempted to put together a map which shows commuting connections between locations in the contiguous United States, using the most fine-grained data I could find. Some of the results of this went into a recent piece in WIRED, and also CityMetric, and the larger piece of work it's based on is part of on-going research into the best ways of mapping commuting flows. The main images are below, followed by some more technical information. For now, all you need to know is that these images show commuting connections of 100 miles or less between Census tracts in the lower 48 states. You'll have to forgive me if your city isn't labelled!
|Higher resolution image available here|
And now some zoomed in versions...
|Zoom in of the west coast|
|Texas, and beyond!|
|Interesting patterns of connectivity in the Midwest|
|Look closely for some interesting inter-connections|
|The famous BosWash megalopolis|
But this just shows where people live, doesn't it? Yes it does. But it also shows how the places where people live connect with other places from a functional economic point of view, at a fairly fine-grained level. It offers a slightly different view than just looking at the urban fabric alone which, I might add, is interesting in itself. Mapping flows like this is not exactly new, as this paper from Arthur Robinson (1955) on Henry Drury Harness (1837) demonstrates. Nonetheless, I haven't seen anyone map travel to work at this resolution for the United States, so I thought I'd have a go myself.
If you spend some time looking at the big version of the map you can begin to see how places connect and where there are obvious disconnections, even between places that are not that far apart. One thing that you can pick up from the complete dataset (but not this batch of maps) is the growth of mega-commuting, as explained by Melanie Rapino and Alison Fields of the United States Census Bureau.
Background information: the data I used is the most recent tract-to-tract journey to work dataset from the American Community Survey. This dataset covers journeys to work between the c74,000 census tracts in the United States and the complete dataset has around 4million interactions. I mapped this in QGIS, using methods I've described previously on this blog. The tricky bits were dealing with the messy FIPS codes, dealing with the size of the dataset, and trying to decide what to label. There is quite a bit of error in the dataset (as acknowledged by the ACS people) and each individual flow line has a margin of error value associated with it, from which I also calculated the coefficient of variation. This is explained in a more detailed working paper, which I expect to publish in the coming months.