The daily commutes of more than 130 million Americans have been used to identify commuter-based megaregions in the United States for the first time, a new paper published in PLOS ONE revealed today (30 November 2016).
While the division into 50 states is how many think of the US, geographers have for the last 50 years also studied networks of closely connected metropolitan areas, known as ‘megaregions’, which often cut across state lines.
Previously megaregions have been typically identified by an interpretative method that links large metropolitan regions through similar environmental and infrastructure systems, economic links and cultural similarities. These approaches are often based on a ‘best guess’ kind of approach, and do not rely on the analysis of large datasets.
Now Dr Alasdair Rae and his co-author Dr Garrett Nelson have developed an empirical approach to identify megaregions using a dataset of more than 4 million ‘commuter flows’ involving the travel to work patterns of 130 million Americans.
The data comes from five-years worth of data from the American Community Survey between 2006 and 2010. The yearly nationwide survey of 3.5 million employees asks where they worked ‘last week’.
Using algorithmic ‘community partitioning’ software developed by the Massachusetts Institute of Technology (MIT) and cloud computing powered by Amazon Web Services, these commuter flows were mapped out and revealed massive labour market areas across the US that form distinct megaregions.
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