Confronta i metodi
Esamina i metodi selezionati fianco a fianco; le righe che differiscono sono evidenziate.
| Analisi dei punti caldi locali (Getis-Ord Gi*)× | I di Moran locali (LISA)× | |
|---|---|---|
| Campo | Analisi spaziale | Analisi spaziale |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 1992-1995 | 1995 |
| Ideatore≠ | Getis & Ord; Ord & Getis | Luc Anselin |
| Tipo≠ | Local spatial statistic | Local spatial autocorrelation statistic |
| Fonte seminale≠ | Ord, J. K., & Getis, A. (1995). Local spatial autocorrelation statistics: Distributional issues and an application. Geographical Analysis, 27(4), 286-306. DOI ↗ | Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| Alias | local Getis-Ord Gi*, Gi* statistic, spatial hot spot detection, local spatial clustering | Local Indicator of Spatial Association, LISA statistic, Anselin Local Moran, local spatial autocorrelation index |
| Correlati≠ | 5 | 6 |
| Sintesi≠ | Local Hot Spot Analysis uses the Getis-Ord Gi* statistic to identify specific geographic locations where high or low values cluster together more than expected by chance. Unlike global measures that return a single summary for the whole study area, this local statistic produces a z-score for each feature, pinpointing exactly where statistically significant hot spots and cold spots occur. | Local Moran's I, introduced by Luc Anselin in 1995, is a Local Indicator of Spatial Association (LISA) that decomposes global spatial autocorrelation into location-specific contributions. For every observation it produces a signed statistic and a significance value, enabling researchers to identify spatial clusters (high-high, low-low) and spatial outliers (high-low, low-high) on a map. |
| ScholarGateInsieme di dati ↗ |
|
|