方法对比
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| 时空盖瑞C指数× | 时空空间自相关× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1954 / 2010s | 1981–1992 |
| 提出者≠ | Geary (1954); extended to space-time by Anselin and others | Cliff & Ord; extended by Anselin and others |
| 类型 | Spatial autocorrelation statistic | Spatial autocorrelation statistic |
| 开创性文献≠ | Geary, R. C. (1954). The Contiguity Ratio and Statistical Mapping. The Incorporated Statistician, 5(3), 115-145. DOI ↗ | Clifford, P., Richardson, S., & Hemon, D. (1989). Assessing the significance of the correlation between two spatial processes. Biometrics, 45(1), 123–134. DOI ↗ |
| 别名 | ST-Geary's C, spatiotemporal Geary C, space-time contiguity ratio, space-time local spatial autocorrelation | STSA, spatiotemporal autocorrelation, space-time Moran's I, temporal spatial dependence |
| 相关≠ | 6 | 5 |
| 摘要≠ | Space-Time Geary's C extends the classical Geary contiguity ratio to panel or longitudinal spatial data, measuring autocorrelation across both geographic neighbors and adjacent time periods simultaneously. Values below 1 indicate positive space-time clustering; values above 1 indicate dispersion, and a value near 1 suggests random arrangement across the space-time lattice. | Space-Time Spatial Autocorrelation extends classic spatial autocorrelation measures — most notably Moran's I — to data that vary across both geographic units and time periods. It detects whether nearby locations that are also temporally close tend to share similar attribute values, revealing clusters, trends, or anomalies that purely spatial or purely temporal analyses would miss. |
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