Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Локальне звичайне крігінґування× | Ко-крігінг: Багатовимірне геостатистичне інтерполювання× | |
|---|---|---|
| Галузь | Просторовий аналіз | Просторовий аналіз |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1970s–1990s | 1965-1978 |
| Автор методу≠ | Journel & Huijbregts; developed further by Goovaerts and Chiles & Delfiner | Matheron, G.; extended by Journel & Huijbregts |
| Тип≠ | Geostatistical interpolation (local/moving-window variant) | Geostatistical interpolation |
| Основоположне джерело≠ | Chiles, J.-P., & Delfiner, P. (1999). Geostatistics: Modeling Spatial Uncertainty. Wiley. ISBN: 978-0471083153 | Journel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910561 |
| Інші назви | moving window kriging, local kriging, neighborhood kriging, LOK | cokriging, co-regionalization kriging, multivariate kriging, CK |
| Пов'язані | 5 | 5 |
| Підсумок≠ | 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. | Co-kriging is a geostatistical interpolation technique that predicts the spatial distribution of a primary variable by leveraging its spatial cross-correlation with one or more secondary (co-) variables. It extends ordinary kriging to multivariate settings, yielding more accurate predictions when the secondary variable is more densely sampled or spatially correlated with the primary variable of interest. |
| ScholarGateНабір даних ↗ |
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