Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| LISA× | Кригинг-интерполяция пространственных данных× | |
|---|---|---|
| Область | Пространственный анализ | Пространственный анализ |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1995 | 1963 |
| Автор метода≠ | Luc Anselin | Georges Matheron (formalised geostatistics) |
| Тип≠ | Local spatial autocorrelation statistic | Geostatistical spatial interpolation |
| Основополагающий источник≠ | Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ | Matheron, G. (1963). Principles of Geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗ |
| Другие названия | local Moran's I, local spatial autocorrelation, LISA cluster analysis, LISA — Yerel Uzamsal Otokorelasyon (Local Moran's I) | geostatistical interpolation, Gaussian process regression (geostatistics), ordinary kriging, Kriging (Mekânsal Enterpolasyon) |
| Связанные | 5 | 5 |
| Сводка≠ | LISA, introduced by Luc Anselin in 1995, is a local statistic that computes spatial autocorrelation separately for every observation rather than for the map as a whole. It pinpoints where high or low values cluster and where spatial outliers sit, decomposing the global Moran's I into a contribution from each location. | Kriging is a geostatistical method that predicts the value of a continuous variable at unmeasured locations from nearby measurements, using the spatial correlation structure captured by a variogram. Formalised by Georges Matheron in 1963, it is the best linear unbiased predictor (BLUP) for spatial data and comes in Ordinary, Universal, and Co-Kriging forms. |
| ScholarGateНабор данных ↗ |
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