Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Krigagem Ordinária Global× | Krigagem Ordinária Local× | |
|---|---|---|
| Área | Análise espacial | Análise espacial |
| Família | Regression model | Regression model |
| Ano de origem≠ | 1951–1963 | 1970s–1990s |
| Autor original≠ | Danie G. Krige; formalized by Georges Matheron | Journel & Huijbregts; developed further by Goovaerts and Chiles & Delfiner |
| Tipo≠ | Geostatistical interpolation | Geostatistical interpolation (local/moving-window variant) |
| Fonte seminal≠ | Cressie, N. A. C. (1993). Statistics for Spatial Data (revised ed.). Wiley. ISBN: 978-0471002550 | Chiles, J.-P., & Delfiner, P. (1999). Geostatistics: Modeling Spatial Uncertainty. Wiley. ISBN: 978-0471083153 |
| Outros nomes | ordinary kriging, OK, global kriging, stationary ordinary kriging | moving window kriging, local kriging, neighborhood kriging, LOK |
| Relacionados | 5 | 5 |
| Resumo≠ | Global Ordinary Kriging (GOK) is the canonical geostatistical interpolation method that estimates values at unsampled locations as a weighted linear combination of nearby observations. It fits a single variogram model to the entire dataset, enforcing a global stationarity assumption, and produces optimal unbiased predictions along with quantified prediction uncertainty at every interpolated point. | Local Ordinary Kriging (LOK) is a geostatistical interpolation method that estimates values at unsampled locations using only a spatially defined moving neighborhood of nearby observations. By restricting each prediction to a local data window rather than the full dataset, LOK accommodates spatial non-stationarity, reduces computational cost, and often yields more accurate local predictions than global ordinary kriging. |
| ScholarGateConjunto de dados ↗ |
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