Measuring inequalities in urban systems: An approach for evaluating the distribution of amenities and burdens

被引:26
|
作者
Logan, T. M. [1 ,4 ]
Anderson, M. J. [1 ,4 ]
Williams, T. G. [2 ]
Conrow, L. [3 ,4 ]
机构
[1] Univ Canterbury, Civil & Nat Resources Engn, Private Bag 4800, Christchurch, New Zealand
[2] Univ Michigan, Ind & Operat Engn, Ann Arbor, MI 48109 USA
[3] Univ Canterbury, Earth & Environm, Christchurch, New Zealand
[4] Univ Canterbury, Cluster Community & Urban Resilience, Christchurch, New Zealand
关键词
Equity; Equality; Environmental justice; Urban planning; Food desert; CLIMATE-CHANGE; ENVIRONMENTAL JUSTICE; HEALTH-BENEFITS; SPATIAL EQUITY; ACCESS; VULNERABILITY; SPACE; ACCESSIBILITY; COMMUNITIES; SERVICES;
D O I
10.1016/j.compenvurbsys.2020.101590
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Current approaches for measuring inequality are insufficient or unsuitable for promoting and designing equitable built environments and urban systems. In this paper, we demonstrate how a recently developed inequality measure-the Kolm-Pollak equally-distributed equivalent (EDE)-could be used to support decision making to foster equity in the built environment. The EDE provides a measure of a distribution that is similar to the average (mean) but includes a penalty based on the inequality of that distribution. The primary advantage of the Kolm-Pollak EDE is that it can be used to evaluate the inequality of both desirable quantities (e.g., amenities) and undesirable quantities (e.g., burdens). This is essential in urban systems as inequities can manifest through, among other things, disparate access to opportunities like public amenities and unequal exposure to burdens, such as pollution and natural hazards. Additionally, the Kolm-Pollak EDE can be calculated for different sociodemographic subgroups, enabling needs-based assessments to promote environmental justice. Thus, the Kolm-Pollak EDE presents numerous opportunities for practitioners, policymakers, and researchers concerned with advancing equity. We demonstrate the approach with a case study of grocery store access in ten cities across the USA and provide a Python package (inequalipy) and R code to enable others to use these inequality metrics.
引用
收藏
页数:11
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