Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/30261
Título: A model of urban scaling laws based on distance dependent interactions
Palavras-chave: Agglomeration effects
Complex systems
Power laws
Scaling laws
Urban indicators
Public policies
Efeitos de aglomeração
Sistemas complexos
Leis de potência
Indicadores urbanos
Políticas públicas
Data do documento: Mar-2017
Editor: Royal Society Publishing
Citação: RIBEIRO, F. L. et al. A model of urban scaling laws based on distance dependent interactions. Royal Society Open Science, [S. l.], v. 4, Mar. 2017. doi: 10.1098/rsos.160926.
Resumo: Socio-economic related properties of a city grow faster than a linear relationship with the population, in a log–log plot, the so-called superlinear scaling. Conversely, the larger a city, the more efficient it is in the use of its infrastructure, leading to a sublinear scaling on these variables. In this work, we addressed a simple explanation for those scaling laws in cities based on the interaction range between the citizens and on the fractal properties of the cities. To this purpose, we introduced a measure of social potential which captured the influence of social interaction on the economic performance and the benefits of amenities in the case of infrastructure offered by the city. We assumed that the population density depends on the fractal dimension and on the distance-dependent interactions between individuals. The model suggests that when the city interacts as a whole, and not just as a set of isolated parts, there is improvement of the socio-economic indicators. Moreover, the bigger the interaction range between citizens and amenities, the bigger the improvement of the socio-economic indicators and the lower the infrastructure costs of the city. We addressed how public policies could take advantage of these properties to improve cities development, minimizing negative effects. Furthermore, the model predicts that the sum of the scaling exponents of social-economic and infrastructure variables are 2, as observed in the literature. Simulations with an agent-based model are confronted with the theoretical approach and they are compatible with the empirical evidences.
URI: http://rsos.royalsocietypublishing.org/content/4/3/160926
http://repositorio.ufla.br/jspui/handle/1/30261
Aparece nas coleções:DFI - Artigos publicados em periódicos

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