Literature DB >> 19706506

Scaling laws between population and facility densities.

Jaegon Um1, Seung-Woo Son, Sung-Ik Lee, Hawoong Jeong, Beom Jun Kim.   

Abstract

When a new facility like a grocery store, a school, or a fire station is planned, its location should ideally be determined by the necessities of people who live nearby. Empirically, it has been found that there exists a positive correlation between facility and population densities. In the present work, we investigate the ideal relation between the population and the facility densities within the framework of an economic mechanism governing microdynamics. In previous studies based on the global optimization of facility positions in minimizing the overall travel distance between people and facilities, it was shown that the density of facility D and that of population rho should follow a simple power law D approximately rho(2/3). In our empirical analysis, on the other hand, the power-law exponent alpha in D approximately rho(alpha) is not a fixed value but spreads in a broad range depending on facility types. To explain this discrepancy in alpha, we propose a model based on economic mechanisms that mimic the competitive balance between the profit of the facilities and the social opportunity cost for populations. Through our simple, microscopically driven model, we show that commercial facilities driven by the profit of the facilities have alpha = 1, whereas public facilities driven by the social opportunity cost have alpha = 2/3. We simulate this model to find the optimal positions of facilities on a real U.S. map and show that the results are consistent with the empirical data.

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Year:  2009        PMID: 19706506      PMCID: PMC2732869          DOI: 10.1073/pnas.0901898106

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  10 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2002-10-04       Impact factor: 11.205

2.  Fractal geometry predicts varying body size scaling relationships for mammal and bird home ranges.

Authors:  John P Haskell; Mark E Ritchie; Han Olff
Journal:  Nature       Date:  2002-08-01       Impact factor: 49.962

3.  The scaling of animal space use.

Authors:  Walter Jetz; Chris Carbone; Jenny Fulford; James H Brown
Journal:  Science       Date:  2004-10-08       Impact factor: 47.728

4.  Optimal design of spatial distribution networks.

Authors:  Michael T Gastner; M E J Newman
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2006-07-24

5.  Geographical networks evolving with an optimal policy.

Authors:  Yan-Bo Xie; Tao Zhou; Wen-Jie Bai; Guanrong Chen; Wei-Ke Xiao; Bing-Hong Wang
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2007-03-08

6.  Territorial division: the least-time constraint behind the formation of subnational boundaries.

Authors:  G E Stephan
Journal:  Science       Date:  1977-04-29       Impact factor: 47.728

7.  Political subdivision and population density.

Authors:  D R Vining; C H Yang; S T Yeh
Journal:  Science       Date:  1979-07-13       Impact factor: 47.728

8.  Price of anarchy in transportation networks: efficiency and optimality control.

Authors:  Hyejin Youn; Michael T Gastner; Hawoong Jeong
Journal:  Phys Rev Lett       Date:  2008-09-17       Impact factor: 9.161

9.  Population dynamic models generating the lognormal species abundance distribution.

Authors:  S Engen; R Lande
Journal:  Math Biosci       Date:  1996-03       Impact factor: 2.144

10.  Nonlinear scaling of space use in human hunter-gatherers.

Authors:  Marcus J Hamilton; Bruce T Milne; Robert S Walker; James H Brown
Journal:  Proc Natl Acad Sci U S A       Date:  2007-03-06       Impact factor: 11.205

  10 in total
  11 in total

1.  Space-time correlations in urban sprawl.

Authors:  A Hernando; R Hernando; A Plastino
Journal:  J R Soc Interface       Date:  2013-11-20       Impact factor: 4.118

2.  Properties of healthcare teaming networks as a function of network construction algorithms.

Authors:  Martin S Zand; Melissa Trayhan; Samir A Farooq; Christopher Fucile; Gourab Ghoshal; Robert J White; Caroline M Quill; Alexander Rosenberg; Hugo Serrano Barbosa; Kristen Bush; Hassan Chafi; Timothy Boudreau
Journal:  PLoS One       Date:  2017-04-20       Impact factor: 3.240

3.  The Non-linear Health Consequences of Living in Larger Cities.

Authors:  Luis E C Rocha; Anna E Thorson; Renaud Lambiotte
Journal:  J Urban Health       Date:  2015-10       Impact factor: 3.671

4.  Is this scaling nonlinear?

Authors:  J C Leitão; J M Miotto; M Gerlach; E G Altmann
Journal:  R Soc Open Sci       Date:  2016-07-13       Impact factor: 2.963

5.  Quantifying Retail Agglomeration using Diverse Spatial Data.

Authors:  Duccio Piovani; Vassilis Zachariadis; Michael Batty
Journal:  Sci Rep       Date:  2017-07-14       Impact factor: 4.379

6.  Urban retail location: Insights from percolation theory and spatial interaction modeling.

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Journal:  PLoS One       Date:  2017-10-04       Impact factor: 3.240

7.  Effects of changing population or density on urban carbon dioxide emissions.

Authors:  Haroldo V Ribeiro; Diego Rybski; Jürgen P Kropp
Journal:  Nat Commun       Date:  2019-07-19       Impact factor: 14.919

8.  Understanding the mesoscopic scaling patterns within cities.

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Journal:  Sci Rep       Date:  2020-12-03       Impact factor: 4.379

9.  Examining the Potential Scaling Law in Urban PM2.5 Pollution Risks along with the Nationwide Air Environmental Effort in China.

Authors:  Lei Yao; Wentian Xu; Ying Xu; Shuo Sun
Journal:  Int J Environ Res Public Health       Date:  2022-04-07       Impact factor: 4.614

10.  Diversity of individual mobility patterns and emergence of aggregated scaling laws.

Authors:  Xiao-Yong Yan; Xiao-Pu Han; Bing-Hong Wang; Tao Zhou
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

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