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Метод обратных взвешенных расстояний (IDW)×Универсальный кригинг (кригинг с трендом)×
ОбластьПространственный анализПространственный анализ
СемействоRegression modelRegression model
Год появления19681969
Автор методаDonald ShepardGeorges Matheron
ТипDeterministic spatial interpolationGeostatistical interpolation with spatial trend
Основополагающий источникShepard, 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 ↗
Другие названияIDW, inverse distance interpolation, Shepard's method, ters mesafe ağırlıklı enterpolasyonkriging with a trend, kriging with drift, trend kriging, evrensel kriging
Связанные33
СводкаInverse 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.
ScholarGateНабор данных
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  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Inverse Distance Weighting · Universal Kriging. Получено 2026-06-19 из https://scholargate.app/ru/compare