Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Локальный анализ горячих точек (Getis-Ord Gi*)× | Локальный индекс пространственной автокорреляции (LISA)× | |
|---|---|---|
| Область | Пространственный анализ | Пространственный анализ |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1992-1995 | 1995 |
| Автор метода≠ | Getis & Ord; Ord & Getis | Luc Anselin |
| Тип≠ | Local spatial statistic | Local spatial autocorrelation statistic |
| Основополагающий источник≠ | 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 ↗ |
| Другие названия | 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 |
| Связанные≠ | 5 | 6 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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