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。
| 局部克里金（移动窗口克里金）× | 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≠ | 1990 | 1965-1978 |
| 提出者≠ | Haas, T. C. | Matheron, G.; extended by Journel & Huijbregts |
| 类型≠ | Spatial interpolation (local variant) | Geostatistical interpolation |
| 开创性文献≠ | Haas, T. C. (1990). Kriging and automated variogram modeling within a moving window. Atmospheric Environment, 24(7), 1759-1769. DOI ↗ | Journel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910561 |
| 别名 | moving-window kriging, local kriging interpolation, windowed kriging, neighborhood kriging | cokriging, co-regionalization kriging, multivariate kriging, CK |
| 相关≠ | 3 | 5 |
| 摘要≠ | Local Kriging is a spatially adaptive geostatistical interpolation method that restricts each prediction to a moving neighborhood of nearby observations, fitting a variogram model locally within that window. This allows spatial covariance structure to vary across the study region rather than imposing a single global variogram, making it better suited to large or non-stationary spatial fields. | 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. |
| ScholarGate数据集 ↗ |
|
|