Regression modelGIS / spatial
协克里金：多元地统计学插值
协克里金（Co-kriging）是一种地统计学插值技术，它通过利用一个主变量与一个或多个次变量（协变量）的空间交叉相关性来预测主变量的空间分布。该方法将普通克里金（ordinary kriging）扩展到多元情境，当次变量采样更密集或与主变量空间相关性更强时，可以获得更精确的预测。
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来源
- Journel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910561
- Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation. Oxford University Press, New York. ISBN: 978-0195115383
如何引用本页
ScholarGate. (2026, June 3). Co-kriging Spatial Interpolation. ScholarGate. https://scholargate.app/zh/spatial-analysis/co-kriging
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 地理加权回归 (GWR)空间分析↔ compare
- 多尺度地理加权回归 (MGWR)空间分析↔ compare
- 普通克里金法空间分析↔ compare
- 空间自相关空间分析↔ compare
- 通用克里金 (带趋势的克里金)空间分析↔ compare