Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Spatial Dissimilarity Index× | Spatial Gini Concentration Index× | |
|---|---|---|
| Область | Human Geography | Human Geography |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1993 | 1991 |
| Автор метода≠ | Richard Morrill & David Wong | Corrado Gini (coefficient); locational adaptation in regional science / economic geography |
| Тип≠ | Boundary-aware index of residential segregation between two groups | Descriptive index of how unevenly an activity is distributed across space |
| Основополагающий источник≠ | Wong, 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 ↗ |
| Другие названия | Spatial Index of Dissimilarity, Adjusted Dissimilarity Index, Boundary-Adjusted Dissimilarity, Spatial Segregation Index | Locational Gini Coefficient, Spatial Gini Index, Geographic Concentration Index, Gini Index of Spatial Inequality |
| Связанные | 4 | 4 |
| Сводка≠ | The 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 spatial (or locational) Gini concentration index adapts the classic Gini coefficient to geography, summarizing in a single number between zero and one how unevenly an activity — an industry, a population group, a resource — is distributed across spatial units relative to a benchmark such as total population or land area. It is the workhorse measure for quantifying geographic concentration and agglomeration in economic geography. |
| ScholarGateНабор данных ↗ |
|
|