XIII.3 Megaregions of the US
Every day, millions of Americans weave together a new geography of commuter patterns. These interlinked megaregions, connected by economic ties, suggest that new kinds of geographic categories are necessary if we wish to accurately describe the functional network of flows and relationships which shape our lives in the modern world.
Megaregions of the US is the work of historical geographer Garrett Dash Nelson, a postdoctoral researcher at Dartmouth College, and Alasdair Rae, an urban and regional data analyst at the University of Sheffield in England. The colorful starbursts are made up of approximately four million lines. Each line shows the linkage of commuters between one census tract and another, with the width proportional to the number of commuters, based on data from the 2010 census. Using an algorithmic technique called community detection to group statistically significant clusters of related places, the map is then divided up into distinct megaregions.
Can you find your own hometown, your own commute, and your new megaregion? Look for places on the map where many commutes cut across megaregional boundaries, and for other places where a single city acts as a center of gravity for commuter traffic. What might our political and planning systems look like if we made these megaregions the basis for dividing up the United States?
Nelson, Garrett D. and Alasdair Rae. 2016. “An Economic Geography of the United States: From Commutes to Megaregions.” PLoS ONE 11(11): e0166083. https://doi.org/10.1371/journal.pone.0166083.
Nelson, Garrett Dash and Alasdair Rae. 2016. Megaregions of the US. Courtesy of Dartmouth College and the University of Sheffield. In “13th Iteration (2017): Macroscopes for Playing with Scale, Places & Spaces: Mapping Science, edited by Katy Börner and Lisel Record. http://scimaps.org.
- What is a Science Map?
- What is a Macroscope?
- Annual Report 2016
- Annual Report 2015
- Annual Report 2014
- Annual Report 2013
- Annual Report 2012
Acknowledgements: This exhibit is supported by the National Science Foundation under Grant No. IIS-0238261, CHE-0524661, IIS-0534909 and IIS-0715303, the James S. McDonnell Foundation; Thomson Reuters; the Cyberinfrastructure for Network Science Center, University Information Technology Services, and the School of Library and Information Science, all three at Indiana University. Some of the data used to generate the science maps is from the Web of Science by Thomson Reuters and Scopus by Elsevier. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.