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| Ко-кригинг: Многовариантна геостатистическа интерполация× | Пространствена автокорелация× | |
|---|---|---|
| Област | Пространствен анализ | Пространствен анализ |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1965-1978 | 1950 |
| Създател≠ | Matheron, G.; extended by Journel & Huijbregts | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| Тип≠ | Geostatistical interpolation | Spatial statistic / exploratory spatial data analysis |
| Основополагащ източник≠ | Journel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910561 | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| Други названия | cokriging, co-regionalization kriging, multivariate kriging, CK | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| Свързани | 5 | 5 |
| Резюме≠ | 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. | Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations. |
| ScholarGateНабор от данни ↗ |
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