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| 全局热点分析（Getis-Ord G统计量）× | 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≠ | 1992 | 1950 |
| 提出者≠ | Arthur Getis and J. Keith Ord | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| 类型≠ | Global spatial concentration test | Spatial statistic / exploratory spatial data analysis |
| 开创性文献≠ | Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206. DOI ↗ | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| 别名 | Global G statistic, Getis-Ord G, global spatial clustering test, global concentration statistic | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| 相关 | 5 | 5 |
| 摘要≠ | Global Hot Spot Analysis uses the Getis-Ord G statistic to determine whether high or low attribute values are spatially concentrated across an entire study area. It answers one question: is there overall clustering of high values (a hot spot tendency) or low values (a cold spot tendency) in the dataset as a whole, producing a single summary test for the full region. | Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations. |
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