方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 局部普通克里金法× | 协克里金：多元地统计学插值× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1970s–1990s | 1965-1978 |
| 提出者≠ | Journel & Huijbregts; developed further by Goovaerts and Chiles & Delfiner | Matheron, G.; extended by Journel & Huijbregts |
| 类型≠ | Geostatistical interpolation (local/moving-window variant) | Geostatistical interpolation |
| 开创性文献≠ | 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 |
| 别名 | moving window kriging, local kriging, neighborhood kriging, LOK | cokriging, co-regionalization kriging, multivariate kriging, CK |
| 相关 | 5 | 5 |
| 摘要≠ | 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. |
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