Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Globale Kriging× | Lokale Kriging (Moving-Window Kriging)× | |
|---|---|---|
| Vakgebied | Ruimtelijke analyse | Ruimtelijke analyse |
| Familie | Regression model | Regression model |
| Jaar van ontstaan≠ | 1960s–1993 | 1990 |
| Grondlegger≠ | Georges Matheron (kriging framework); global neighborhood usage formalized in applied geostatistics | Haas, T. C. |
| Type≠ | Geostatistical interpolation | Spatial interpolation (local variant) |
| Oorspronkelijke bron≠ | Cressie, N. A. C. (1993). Statistics for Spatial Data (revised ed.). Wiley-Interscience. ISBN: 978-0471002550 | Haas, T. C. (1990). Kriging and automated variogram modeling within a moving window. Atmospheric Environment, 24(7), 1759-1769. DOI ↗ |
| Aliassen | global-neighborhood kriging, full-data kriging, exhaustive kriging, non-local kriging | moving-window kriging, local kriging interpolation, windowed kriging, neighborhood kriging |
| Verwant≠ | 5 | 3 |
| Samenvatting≠ | Global Kriging is the ordinary kriging interpolation procedure applied using all available sample points as the neighborhood — no spatial search window limits which data contribute to each prediction. It produces optimal linear unbiased predictions of an unobserved value at any target location, with associated prediction-error variances, by exploiting a fitted variogram model that encodes spatial autocorrelation across the entire dataset. | 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. |
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