2010
DOI: 10.1177/0891242410383414
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Measuring Spatial Dynamics in Metropolitan Areas

Abstract: This article introduces a new approach to measuring neighborhood change. Instead of the traditional method of identifying “neighborhoods” a priori and then studying how resident attributes change over time, this approach looks at the neighborhood more intrinsically as a unit that has both a geographic footprint and a socioeconomic composition. Therefore, change is identified when both aspects of a neighborhood transform from one period to the next. The approach is based on a spatial clustering algorithm that i… Show more

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Cited by 35 publications
(26 citation statements)
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“…We know that neighborhoods have momentum and that both improvement and decline of neighborhoods follow spatial patterns that are frequently represented by diffusion or contagion models (Rey & Anselin, 2011; van Ham et al, 2012). Multi-scalar segregation may help us represent how processes are transmitted.…”
Section: Discussionmentioning
confidence: 99%
“…We know that neighborhoods have momentum and that both improvement and decline of neighborhoods follow spatial patterns that are frequently represented by diffusion or contagion models (Rey & Anselin, 2011; van Ham et al, 2012). Multi-scalar segregation may help us represent how processes are transmitted.…”
Section: Discussionmentioning
confidence: 99%
“…[57]. Generally speaking, these methods use demographic characteristics of the initial areas to create clusters of homogeneous, contiguous regions [58]. Although a number of methods have been proposed for creating small-areas, these were deemed inappropriate for our study.…”
Section: Methodsmentioning
confidence: 99%
“…Analytical regions were delineated by grouping the administrative neighborhoods using the Max-PRegions algorithm in ClusterPy software (Juan C. Duque, Dev, Betancourt, & Franco, 2011;Juan Carlos Duque, Anselin, & Rey, 2012). 1 This process has been used in previous research on the urban spatial structure and spatial dynamics of major U.S. metropolitan areas (Arribas-Bel & Schmidt, 2013;Rey et al, 2011), pediatric mortality in Brazil (Leyk, Norlund, & Nuckols, 2012), interregional inequality in Mexico (Rey & Sastré-Gutiérrez, 2010), intraurban inequalities in Accra, Ghana (Stow, Lippitt, & Weeks, 2010;Weeks, Hill, Stow, Getis, & Fugate, 2006;Weeks et al, 2007), and intra-urban poverty in Medellin, Colombia (Juan C. Duque et al, 2013). Regionalization can reduce the spurious spatial autocorrelation that is present when analyzing smaller administrative spatial units (Weeks et al, 2007).…”
Section: Spatial Unit Of Analysismentioning
confidence: 99%