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| Multiscale Getis-Ord Gi* Hot Spot Analysis× | Rumlig Autokorrelation× | |
|---|---|---|
| Fagområde | Rumlig analyse | Rumlig analyse |
| Familie | Regression model | Regression model |
| Oprindelsesår≠ | 1995 (Gi* basis); multiscale application 2000s onward | 1950 |
| Ophavsperson≠ | Ord & Getis (1995); multiscale extension developed in applied spatial analysis practice | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| Type≠ | Local spatial statistic (multiscale) | Spatial statistic / exploratory spatial data analysis |
| Oprindelig kilde≠ | Ord, J. K., & Getis, A. (1995). Local spatial autocorrelation statistics: Distributional issues and an application. Geographical Analysis, 27(4), 286-306. DOI ↗ | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| Aliasser | multi-distance Gi*, multiscale hot spot analysis, multi-bandwidth Getis-Ord, scale-varying Gi* | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| Relaterede | 5 | 5 |
| Resumé≠ | Multiscale Getis-Ord Gi* extends the classic local hot spot statistic by computing Gi* z-scores across a range of spatial distance bands or neighborhood sizes. This reveals whether clusters of high or low values are scale-dependent — appearing only at fine local scales, only at broad regional scales, or persistently across all scales — providing richer spatial intelligence than a single-bandwidth analysis. | 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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