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Spatial Dissimilarity Index×Index of Dissimilarity×
FieldHuman GeographySociology
FamilyProcess / pipelineProcess / pipeline
Year of origin19931955
OriginatorRichard Morrill & David WongOtis Dudley Duncan & Beverly Duncan
TypeBoundary-aware index of residential segregation between two groupsIndex of evenness of two groups across units
Seminal sourceWong, D. W. S. (1993). Spatial indices of segregation. Urban Studies, 30(3), 559–572. DOI ↗Duncan, O. D., & Duncan, B. (1955). A methodological analysis of segregation indexes. American Sociological Review, 20(2), 210–217. DOI ↗
AliasesSpatial Index of Dissimilarity, Adjusted Dissimilarity Index, Boundary-Adjusted Dissimilarity, Spatial Segregation Indexdissimilarity index, Duncan index, D index, segregation index
Related45
SummaryThe spatial dissimilarity index is a boundary-aware measure of residential segregation that corrects the classic index of dissimilarity for the fact that areal units are not isolated boxes but neighbours that share borders. Developed by Richard Morrill in 1991 and refined by David Wong in 1993, it discounts the aspatial index by the degree to which adjacent units differ in group composition, so that two groups clustered into separate but neighbouring areas are recorded as less segregated than two groups locked into a checkerboard. It directly addresses the long-standing checkerboard problem that the aspatial Duncan index cannot see.The index of dissimilarity, often called the Duncan segregation index, measures how unevenly two groups — such as two racial or occupational groups — are distributed across a set of units like neighborhoods, schools, or occupations. It ranges from 0, when both groups have identical distributions across units, to 1, when the units are completely segregated, and has the intuitive interpretation of the share of one group that would have to relocate to achieve an even distribution.
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ScholarGateCompare methods: Spatial Dissimilarity Index · Index of Dissimilarity. Retrieved 2026-06-24 from https://scholargate.app/en/compare