空间分析
索引(排版)
空间生态学
差异指数
空间变异性
人口
集合(抽象数据类型)
空间相关性
聚类分析
度量(数据仓库)
空间分布
统计
计算机科学
数学
数据挖掘
生态学
万维网
社会学
人口学
生物
程序设计语言
作者
Sean F. Reardon,David O’Sullivan
标识
DOI:10.1111/j.0081-1750.2004.00150.x
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI