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Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities
With urban population increasing dramatically worldwide, cities are playing an increasingly critical role in human societies and the sustainability of the planet. An obstacle to effective policy is the lack of meaningful urban metrics based on a quantitative understanding of cities. Typically, linea...
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2978092/ https://www.ncbi.nlm.nih.gov/pubmed/21085659 http://dx.doi.org/10.1371/journal.pone.0013541 |
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author | Bettencourt, Luís M. A. Lobo, José Strumsky, Deborah West, Geoffrey B. |
author_facet | Bettencourt, Luís M. A. Lobo, José Strumsky, Deborah West, Geoffrey B. |
author_sort | Bettencourt, Luís M. A. |
collection | PubMed |
description | With urban population increasing dramatically worldwide, cities are playing an increasingly critical role in human societies and the sustainability of the planet. An obstacle to effective policy is the lack of meaningful urban metrics based on a quantitative understanding of cities. Typically, linear per capita indicators are used to characterize and rank cities. However, these implicitly ignore the fundamental role of nonlinear agglomeration integral to the life history of cities. As such, per capita indicators conflate general nonlinear effects, common to all cities, with local dynamics, specific to each city, failing to provide direct measures of the impact of local events and policy. Agglomeration nonlinearities are explicitly manifested by the superlinear power law scaling of most urban socioeconomic indicators with population size, all with similar exponents ([Image: see text]1.15). As a result larger cities are disproportionally the centers of innovation, wealth and crime, all to approximately the same degree. We use these general urban laws to develop new urban metrics that disentangle dynamics at different scales and provide true measures of local urban performance. New rankings of cities and a novel and simpler perspective on urban systems emerge. We find that local urban dynamics display long-term memory, so cities under or outperforming their size expectation maintain such (dis)advantage for decades. Spatiotemporal correlation analyses reveal a novel functional taxonomy of U.S. metropolitan areas that is generally not organized geographically but based instead on common local economic models, innovation strategies and patterns of crime. |
format | Text |
id | pubmed-2978092 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-29780922010-11-17 Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities Bettencourt, Luís M. A. Lobo, José Strumsky, Deborah West, Geoffrey B. PLoS One Research Article With urban population increasing dramatically worldwide, cities are playing an increasingly critical role in human societies and the sustainability of the planet. An obstacle to effective policy is the lack of meaningful urban metrics based on a quantitative understanding of cities. Typically, linear per capita indicators are used to characterize and rank cities. However, these implicitly ignore the fundamental role of nonlinear agglomeration integral to the life history of cities. As such, per capita indicators conflate general nonlinear effects, common to all cities, with local dynamics, specific to each city, failing to provide direct measures of the impact of local events and policy. Agglomeration nonlinearities are explicitly manifested by the superlinear power law scaling of most urban socioeconomic indicators with population size, all with similar exponents ([Image: see text]1.15). As a result larger cities are disproportionally the centers of innovation, wealth and crime, all to approximately the same degree. We use these general urban laws to develop new urban metrics that disentangle dynamics at different scales and provide true measures of local urban performance. New rankings of cities and a novel and simpler perspective on urban systems emerge. We find that local urban dynamics display long-term memory, so cities under or outperforming their size expectation maintain such (dis)advantage for decades. Spatiotemporal correlation analyses reveal a novel functional taxonomy of U.S. metropolitan areas that is generally not organized geographically but based instead on common local economic models, innovation strategies and patterns of crime. Public Library of Science 2010-11-10 /pmc/articles/PMC2978092/ /pubmed/21085659 http://dx.doi.org/10.1371/journal.pone.0013541 Text en Bettencourt et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Bettencourt, Luís M. A. Lobo, José Strumsky, Deborah West, Geoffrey B. Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities |
title | Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities |
title_full | Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities |
title_fullStr | Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities |
title_full_unstemmed | Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities |
title_short | Urban Scaling and Its Deviations: Revealing the Structure of Wealth, Innovation and Crime across Cities |
title_sort | urban scaling and its deviations: revealing the structure of wealth, innovation and crime across cities |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2978092/ https://www.ncbi.nlm.nih.gov/pubmed/21085659 http://dx.doi.org/10.1371/journal.pone.0013541 |
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