Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Глобальный универсальный кригинг× | Кокригинг: Многомерная геостатистическая интерполяция× | |
|---|---|---|
| Область | Пространственный анализ | Пространственный анализ |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1969 | 1965-1978 |
| Автор метода≠ | Georges Matheron | Matheron, G.; extended by Journel & Huijbregts |
| Тип | Geostatistical interpolation | Geostatistical interpolation |
| Основополагающий источник | Journel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910608 | Journel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Academic Press, London. ISBN: 978-0123910561 |
| Другие названия | universal kriging (global), global UK, kriging with external drift (global), global trend kriging | cokriging, co-regionalization kriging, multivariate kriging, CK |
| Связанные≠ | 4 | 5 |
| Сводка≠ | Global Universal Kriging is a geostatistical interpolation method that models a spatially varying trend (drift) as a deterministic function of coordinates and uses the entire dataset to fit both the trend coefficients and the residual variogram simultaneously. It produces optimal linear unbiased predictions together with pointwise estimation uncertainty, accounting for a large-scale spatial gradient across the full study region. | 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. |
| ScholarGateНабор данных ↗ |
|
|