Abstract

We show here that population growth, resolved at the county level, is spatially heterogeneous both among and within the U.S. metropolitan statistical areas. Our analysis of data for over 3,100 U.S. counties reveals that annual population flows, resulting from domestic migration during the 2015–2019 period, are much larger than natural demographic growth, and are primarily responsible for this heterogeneous growth. More precisely, we show that intra-city flows are generally along a negative population density gradient, while inter-city flows are concentrated in high-density core areas. Intra-city flows are anisotropic and generally directed towards external counties of cities, driving asymmetrical urban sprawl. Such domestic migration dynamics are also responsible for tempering local population shocks by redistributing inflows within a given city. This spill-over effect leads to a smoother population dynamics at the county level, in contrast to that observed at the city level. Understanding the spatial structure of domestic migration flows is a key ingredient for analyzing their drivers and consequences, thus representing a crucial knowledge for urban policy makers and planners.

A new study finds that city growth in the U.S. is spatially heterogeneous. Inter-city flows concentrate in core areas. Intra-city flows are generally directed towards external and low density counties of cities, and is the main contributor to urban sprawl.

Details

Title
Spatial structure of city population growth
Author
Reia, Sandro M. 1   VIAFID ORCID Logo  ; Rao, P. Suresh C. 2   VIAFID ORCID Logo  ; Barthelemy, Marc 3   VIAFID ORCID Logo  ; Ukkusuri, Satish V. 1   VIAFID ORCID Logo 

 Purdue University, Lyles School of Civil Engineering, West Lafayette, USA (GRID:grid.169077.e) (ISNI:0000 0004 1937 2197) 
 Purdue University, Lyles School of Civil Engineering, West Lafayette, USA (GRID:grid.169077.e) (ISNI:0000 0004 1937 2197); Purdue University, Agronomy Department, West Lafayette, USA (GRID:grid.169077.e) (ISNI:0000 0004 1937 2197) 
 Université Paris-Saclay, CNRS, CEA, Institut de physique théorique, Gif-surYvette, France (GRID:grid.4444.0) (ISNI:0000 0001 2112 9282); Centre d’Analyse et de Mathématique Sociales, CNRS/EHESS, Paris, France (GRID:grid.463832.8) (ISNI:0000 0001 2289 0700) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2722750341
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.