Salīdzināt metodes
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| Getis-Ord Gi* statistika laika un telpā× | Karstā punkta analīze (Getis-Ord Gi*)× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1992 (Gi*); space-time extension ~2000s–2010s | 1992 |
| Autors≠ | Getis & Ord (seminal); space-time extension developed in GIS literature and ArcGIS Emerging Hot Spot Analysis | Arthur Getis and J. Keith Ord |
| Tips≠ | Local spatial statistic (space-time extension) | Local spatial statistic |
| Pirmavots | Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206. DOI ↗ | Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206. DOI ↗ |
| Citi nosaukumi | ST-Gi*, space-time hot spot analysis, emerging hot spot analysis, space-time local autocorrelation statistic | Getis-Ord Gi* statistic, spatial hot spot detection, cluster and outlier analysis, HSA |
| Saistītās≠ | 4 | 5 |
| Kopsavilkums≠ | The Space-Time Getis-Ord Gi* statistic extends the classic Gi* local hot spot measure into three dimensions — two spatial and one temporal — revealing not only where concentrations of high or low values cluster, but how those clusters evolve, intensify, or diminish over time. It is widely used in crime analysis, epidemiology, ecology, and urban studies. | Hot Spot Analysis uses the Getis-Ord Gi* local spatial statistic to identify geographic locations where high or low attribute values cluster together to a degree that is statistically significant. Each feature is evaluated in relation to its neighbours, producing a z-score that flags genuine spatial hot spots and cold spots against a background of random variation. |
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