Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Accessibility Equity Analysis× | Urban Network Analysis× | |
|---|---|---|
| Область | Urban Studies | Urban Studies |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2004 | 2012 |
| Автор метода≠ | Karst Geurs & Bert van Wee (accessibility evaluation framework) | Andres Sevtsuk & Michael Mekonnen |
| Тип≠ | Distributional analysis of accessibility across population groups | Graph-based centrality analysis of spatial urban networks |
| Основополагающий источник≠ | Geurs, K. T., & van Wee, B. (2004). Accessibility evaluation of land-use and transport strategies: review and research directions. Journal of Transport Geography, 12(2), 127–140. DOI ↗ | Sevtsuk, A., & Mekonnen, M. (2012). Urban network analysis: A new toolbox for ArcGIS. Revue Internationale de Géomatique, 22(2), 287–305. DOI ↗ |
| Другие названия | Distributional Accessibility Analysis, Transport Equity Analysis, Access Equity Assessment, Accessibility Gini Analysis | UNA Toolbox, Spatial Network Centrality, Building-Level Network Analysis, Street Network Centrality Analysis |
| Связанные | 4 | 4 |
| Сводка≠ | Accessibility equity analysis asks not just how much access to opportunities a place has, but how that access is distributed across people and social groups — who can reach jobs, healthcare, and education, and who is left behind. It pairs an accessibility measure, in the tradition formalized by Karst Geurs and Bert van Wee, with the distributional tools of inequality measurement: Lorenz curves, Gini and Palma indices, and comparisons between advantaged and disadvantaged groups. The result reframes accessibility as a question of fairness, revealing whether a transport or land-use arrangement concentrates reachable opportunity among the already privileged or spreads it equitably. | Urban network analysis treats a city as a spatial graph of streets and buildings and measures the centrality of each location — how reachable, how central, and how well-connected it is along the actual travel network. Formalized in the Urban Network Analysis toolbox by Andres Sevtsuk and Michael Mekonnen in 2012, it differs from generic network science by weighting graph nodes with real urban data such as building floor area or population and by computing centralities within bounded search radii. The result is a set of metrics — reach, gravity, betweenness, closeness, straightness — that quantify the structural role of every building or street segment in the urban fabric. |
| ScholarGateНабор данных ↗ |
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