Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Универсальный кригинг (кригинг с трендом)× | Метод обратных взвешенных расстояний (IDW)× | |
|---|---|---|
| Область | Пространственный анализ | Пространственный анализ |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1969 | 1968 |
| Автор метода≠ | Georges Matheron | Donald Shepard |
| Тип≠ | Geostatistical interpolation with spatial trend | Deterministic spatial interpolation |
| Основополагающий источник≠ | Matheron, G. (1963). Principles of geostatistics. Economic Geology, 58(8), 1246–1266. DOI ↗ | Shepard, D. (1968). A two-dimensional interpolation function for irregularly-spaced data. Proceedings of the 23rd ACM National Conference, 517–524. DOI ↗ |
| Другие названия | kriging with a trend, kriging with drift, trend kriging, evrensel kriging | IDW, inverse distance interpolation, Shepard's method, ters mesafe ağırlıklı enterpolasyon |
| Связанные | 3 | 3 |
| Сводка≠ | 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. | 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. |
| ScholarGateНабор данных ↗ |
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