Nelson, G.D. and Rae, A.J. orcid.org/0000-0003-0136-7659 (2016) An economic geography of the United States: from commutes to megaregions. PLoS One, 11 (11). e0166083. ISSN 1932-6203
Abstract
The emergence in the United States of large-scale “megaregions” centered on major metropolitan areas is a phenomenon often taken for granted in both scholarly studies and popular accounts of contemporary economic geography. This paper uses a data set of more than 4,000,000 commuter flows as the basis for an empirical approach to the identification of such megaregions. We compare a method which uses a visual heuristic for understanding areal aggregation to a method which uses a computational partitioning algorithm, and we reflect upon the strengths and limitations of both. We discuss how choices about input parameters and scale of analysis can lead to different results, and stress the importance of comparing computational results with “common sense” interpretations of geographic coherence. The results provide a new perspective on the functional economic geography of the United States from a megaregion perspective, and shed light on the old geographic problem of the division of space into areal units.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Dash Nelson, Rae. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Urban Studies & Planning (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Nov 2016 16:26 |
Last Modified: | 21 Jan 2020 11:40 |
Published Version: | https://doi.org/10.1371/journal.pone.0166083 |
Status: | Published |
Publisher: | Public Library of Science |
Refereed: | Yes |
Identification Number: | 10.1371/journal.pone.0166083 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:106931 |