3. Measures of Spatial Segregation

TLDR

Residential segregation measurement has been constrained by tools that ignore spatial patterning of population distributions. This paper introduces a general approach for measuring spatial segregation among multiple population groups. The framework allows researchers to define any spatial proximity concept and compute a suite of indices—including a spatial exposure/isolation index and several multigroup evenness/clustering measures—which are then evaluated against eight desirable properties. The authors conclude that the spatial exposure/isolation index and the spatial information theory index best satisfy conceptual and mathematical criteria among the proposed spatial indices.

Abstract

The measurement of residential segregation patterns and trends has been limited by a reliance on segregation measures that do not appropriately take into account the spatial patterning of population distributions. In this paper we define a general approach to measuring spatial segregation among multiple population groups. This general approach allows researchers to specify any theoretically based definition of spatial proximity desired in computing segregation measures. Based on this general approach, we develop a general spatial exposure/isolation index ( ), and a set of general multigroup spatial evenness/clustering indices: a spatial information theory index ( ), a spatial relative diversity index ( ), and a spatial dissimilarity index ( ). We review these and previously proposed spatial segregation indices against a set of eight desirable properties of spatial segregation indices. We conclude that the spatial exposure/isolation index *—which can be interpreted as a measure of the average composition of individuals' local spatial environments—and the spatial information theory index —which can be interpreted as a measure of the variation in the diversity of the local spatial environments of each individual—are the most conceptually and mathematically satisfactory of the proposed spatial indices.