Urban growth tendency of electrical cables in the Costa Rican Metropolitan Area

Abstract In modern society, the majority of the population lives in cities. Thus, it becomes relevant to be able to predict the growth of social indicators and infrastructure, among other factors, in order to make proper decisions for the city’s development. Such a prediction can be obtained by means of an appropriate mathematical model that describes this growth. However, cities are complex systems influenced by many variables, and it is difficult to obtain precise mathematical descriptions for them. Nevertheless, it was found that the growth of numerous urban indicators can be described as a function of population given by a power law, and that the growth of infrastructure in most cities obeys a sublinear power law with an exponent close to 0.8. In this research, we verify the sublinear power tendency of the infrastructure development in Costa Rica, presented as the scaling of electrical cable length. We obtain for the first time experimental evidence on the power scaling laws corresponding to the growth of electrical cable length for two cities in San Jose Province, Costa Rica, and compare them with the one presented for Germany. This provides a first model for the prediction of electrical cable growth in the Costa Rican Metropolitan Area, and enables the possibility of using the same methods to obtain the growth tendency of other types of infrastructure.

[1]  Horacio Samaniego,et al.  Scaling and universality in urban economic diversification , 2016, Journal of The Royal Society Interface.

[2]  Luís M. A. Bettencourt,et al.  Why are large cities faster? Universal scaling and self-similarity in urban organization and dynamics , 2008 .

[3]  K. Seto,et al.  The New Geography of Contemporary Urbanization and the Environment , 2010 .

[4]  Zbigniew Smoreda,et al.  The scaling of human interactions with city size , 2012, Journal of The Royal Society Interface.

[5]  D. Helbing,et al.  Growth, innovation, scaling, and the pace of life in cities , 2007, Proceedings of the National Academy of Sciences.

[6]  Michael Batty,et al.  Defining City Size , 2011 .

[7]  N. Wertheimer,et al.  Adult cancer related to electrical wires near the home. , 1982, International journal of epidemiology.

[8]  Martí Rosas-Casals,et al.  Discerning Electricity Consumption Patterns from Urban Allometric Scaling , 2010, 2010 Complexity in Engineering.

[9]  M. Batty,et al.  Building a science of cities , 2012 .

[10]  L. Bettencourt,et al.  Urban geography and scaling of contemporary Indian cities , 2018, Journal of the Royal Society Interface.

[11]  Michael Batty,et al.  An overview of city analytics , 2017, Royal Society Open Science.

[12]  S. Pincetl,et al.  An expanded urban metabolism method: Toward a systems approach for assessing urban energy processes and causes , 2012 .

[13]  M. Moses,et al.  Cities as Organisms: Allometric Scaling of Urban Road Networks , 2008 .

[14]  L. Bettencourt,et al.  Urban Scaling and the Production Function for Cities , 2013, PloS one.

[15]  D. Korosak,et al.  Superlinear and sublinear urban scaling in geographical networks modeling cities. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  Tracey P. Lauriault,et al.  Knowing and governing cities through urban indicators, city benchmarking and real-time dashboards , 2015 .

[17]  L. Bettencourt,et al.  Urban scaling in Europe , 2015, Journal of The Royal Society Interface.

[18]  Fernando F Ferreira,et al.  A model of urban scaling laws based on distance dependent interactions , 2017, Royal Society Open Science.

[19]  Marc Barthelemy,et al.  From global scaling to the dynamics of individual cities , 2017, Proceedings of the National Academy of Sciences.

[20]  Zhao Yang Dong,et al.  Analysis of electric field influence on buildings under high-voltage transmission lines , 2016 .