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Scaling Laws in City Growth: Setting Limitations with Self-Organizing Maps

Do scaling relations always provide the means to anticipate the relationships between the size of cities, costs of maintenance, and the socio-economic benefits resulting from their growth? Scaling laws are considered a universal principle that describes the development of complex systems such as cit...

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Detalles Bibliográficos
Autores principales: Cebrat, Krzysztof, Sobczyński, Maciej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5179107/
https://www.ncbi.nlm.nih.gov/pubmed/28005994
http://dx.doi.org/10.1371/journal.pone.0168753
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author Cebrat, Krzysztof
Sobczyński, Maciej
author_facet Cebrat, Krzysztof
Sobczyński, Maciej
author_sort Cebrat, Krzysztof
collection PubMed
description Do scaling relations always provide the means to anticipate the relationships between the size of cities, costs of maintenance, and the socio-economic benefits resulting from their growth? Scaling laws are considered a universal principle that describes the development of complex systems such as cities. It seems that regardless of their location or history, the growth of cities is associated with the super-linear or sublinear scaling of features such as the amount of space required, infrastructure, or human activities. However, the results of our research, based on grouping by Self-Organizing Maps, reveal some limitations in the application of scaling laws: the trends of urban growth behave in a different manner when we consider both a large and diverse collection of cities and a subset of cities alike. This finding complements the existing body of knowledge on the growth of cities and allows for a more accurate prediction of their future.
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spelling pubmed-51791072017-01-04 Scaling Laws in City Growth: Setting Limitations with Self-Organizing Maps Cebrat, Krzysztof Sobczyński, Maciej PLoS One Research Article Do scaling relations always provide the means to anticipate the relationships between the size of cities, costs of maintenance, and the socio-economic benefits resulting from their growth? Scaling laws are considered a universal principle that describes the development of complex systems such as cities. It seems that regardless of their location or history, the growth of cities is associated with the super-linear or sublinear scaling of features such as the amount of space required, infrastructure, or human activities. However, the results of our research, based on grouping by Self-Organizing Maps, reveal some limitations in the application of scaling laws: the trends of urban growth behave in a different manner when we consider both a large and diverse collection of cities and a subset of cities alike. This finding complements the existing body of knowledge on the growth of cities and allows for a more accurate prediction of their future. Public Library of Science 2016-12-22 /pmc/articles/PMC5179107/ /pubmed/28005994 http://dx.doi.org/10.1371/journal.pone.0168753 Text en © 2016 Cebrat, Sobczyński http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Cebrat, Krzysztof
Sobczyński, Maciej
Scaling Laws in City Growth: Setting Limitations with Self-Organizing Maps
title Scaling Laws in City Growth: Setting Limitations with Self-Organizing Maps
title_full Scaling Laws in City Growth: Setting Limitations with Self-Organizing Maps
title_fullStr Scaling Laws in City Growth: Setting Limitations with Self-Organizing Maps
title_full_unstemmed Scaling Laws in City Growth: Setting Limitations with Self-Organizing Maps
title_short Scaling Laws in City Growth: Setting Limitations with Self-Organizing Maps
title_sort scaling laws in city growth: setting limitations with self-organizing maps
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5179107/
https://www.ncbi.nlm.nih.gov/pubmed/28005994
http://dx.doi.org/10.1371/journal.pone.0168753
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