方法对比
并排查看您选择的方法;存在差异的行会高亮显示。
| Mixed-Use Index× | Urban Scaling Laws× | |
|---|---|---|
| 领域 | Urban Studies | Urban Studies |
| 方法族≠ | Process / pipeline | Regression model |
| 起源年份≠ | 1997 | 2007 |
| 提出者≠ | Cervero & Kockelman (land-use diversity / 3Ds); Frank et al. (entropy walkability term) | Luís Bettencourt & Geoffrey West |
| 类型≠ | Index of how evenly land uses are mixed within an area | Power-law regression of urban indicators against population size |
| 开创性文献≠ | Cervero, R., & Kockelman, K. (1997). Travel demand and the 3Ds: density, diversity, and design. Transportation Research Part D: Transport and Environment, 2(3), 199–219. DOI ↗ | Bettencourt, L. M. A., Lobo, J., Helbing, D., Kühnert, C., & West, G. B. (2007). Growth, innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences, 104(17), 7301–7306. DOI ↗ |
| 别名 | Land-Use Mix Entropy, Land-Use Diversity Index, Herfindahl Land-Use Index, Entropy Land-Use Mix | Urban Scaling, Settlement Scaling Theory, Power-Law Urban Scaling, Superlinear and Sublinear Urban Scaling |
| 相关 | 4 | 4 |
| 摘要≠ | A mixed-use index measures how evenly different land uses — residential, retail, office, civic, industrial — are blended within an area, turning the planning ideal of vibrant, walkable mixed-use districts into a number. The dominant formulation borrows the entropy measure from information theory: a value near zero when one use dominates and near one when uses are perfectly balanced. Popularised through the 'density, diversity, design' framework of Cervero and Kockelman and embedded in walkability indices by Frank and colleagues, these indices quantify land-use diversity for studies of travel behaviour, walkability and urban vitality. | Urban scaling laws describe how the aggregate properties of cities — wealth, innovation, infrastructure, crime — change systematically with population size, following power laws rather than growing in simple proportion. Building on the 2007 work of Luís Bettencourt, Geoffrey West and colleagues, the framework shows that socioeconomic outputs typically scale superlinearly (a doubling of population more than doubles GDP and patents) while infrastructure scales sublinearly (larger cities need proportionally fewer roads and cables per person), with a single exponent β capturing the regularity across an entire urban system. |
| ScholarGate数据集 ↗ |
|
|