On the relation between transversal and longitudinal scaling in cities

PLoS One. 2020 May 19;15(5):e0233003. doi: 10.1371/journal.pone.0233003. eCollection 2020.

Abstract

Does the scaling relationship between population sizes of cities with urban metrics like economic output and infrastructure (transversal scaling) mirror the evolution of individual cities in time (longitudinal scaling)? The answer to this question has important policy implications, but the lack of suitable data has so far hindered rigorous empirical tests. In this paper, we advance the debate by looking at the evolution of two urban variables, GDP and water network length, for over 5500 cities in Brazil. We find that longitudinal scaling exponents are city-specific. However, they are distributed around an average value that approaches the transversal scaling exponent provided that the data is decomposed to eliminate external factors, and only for cities with a sufficiently high growth rate. We also introduce a mathematical framework that connects the microscopic level to global behaviour, finding good agreement between theoretical predictions and empirical evidence in all analyzed cases. Our results add complexity to the idea that the longitudinal dynamics is a micro-scaling version of the transversal dynamics of the entire urban system. The longitudinal analysis can reveal differences in scaling behavior related to population size and nature of urban variables. Our approach also makes room for the role of external factors such as public policies and development, and opens up new possibilities in the research of the effects of scaling and contextual factors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brazil
  • Cities / economics
  • Cities / statistics & numerical data
  • Gross Domestic Product / statistics & numerical data
  • Humans
  • Longitudinal Studies
  • Models, Statistical
  • Population Density*
  • Population Growth
  • Public Policy
  • Urban Population / statistics & numerical data*
  • Urban Renewal / economics
  • Urban Renewal / statistics & numerical data
  • Urbanization*
  • Water Supply / statistics & numerical data

Grants and funding

This work was supported by École polytechnique fédérale de Lausanne (Joao Meirelles), Conselho Nacional de Desenvolvimento Científico e Tecnológico (Fabiano Lemes Ribeiro, process number: 405921/2016-0), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Fabiano Lemes Ribeiro, process number: 88881.119533/2016-01). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.