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| Inverse Distance Weighting (IDW)× | Universelles Kriging (Kriging mit Trend)× | |
|---|---|---|
| Fachgebiet | Räumliche Analyse | Räumliche Analyse |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 1968 | 1969 |
| Urheber≠ | Donald Shepard | Georges Matheron |
| Typ≠ | Deterministic spatial interpolation | Geostatistical interpolation with spatial trend |
| Wegweisende Quelle≠ | Shepard, D. (1968). A two-dimensional interpolation function for irregularly-spaced data. Proceedings of the 23rd ACM National Conference, 517–524. DOI ↗ | Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗ |
| Aliasnamen | IDW, inverse distance interpolation, Shepard's method, ters mesafe ağırlıklı enterpolasyon | kriging with a trend, kriging with drift, trend kriging, evrensel kriging |
| Verwandt | 3 | 3 |
| Zusammenfassung≠ | Inverse distance weighting is a simple, deterministic method for estimating values at unsampled locations by taking a weighted average of nearby measured points, where closer points carry more weight. Introduced by Donald Shepard in 1968, it embodies the first law of geography — near things are more related than distant things — and is one of the most widely used interpolation methods in GIS for mapping continuous fields such as rainfall, elevation, or pollution from scattered samples. | Universal kriging generalizes ordinary kriging to data whose mean varies systematically across space — a spatial trend or 'drift'. It models the mean as a function of the coordinates (or covariates) and krigs the residuals, so it can interpolate variables that drift in a preferred direction, such as temperature falling with latitude or a pollutant gradient, while still returning prediction variances. |
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