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Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.

Crinaj universal (Crinaj cu tendință)×Ponderarea inversă a distanței (IDW)×
DomeniuAnaliză spațialăAnaliză spațială
FamilieRegression modelRegression model
Anul apariției19691968
Autorul originalGeorges MatheronDonald Shepard
TipGeostatistical interpolation with spatial trendDeterministic spatial interpolation
Sursa seminalăMatheron, 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 ↗
Denumiri alternativekriging with a trend, kriging with drift, trend kriging, evrensel krigingIDW, inverse distance interpolation, Shepard's method, ters mesafe ağırlıklı enterpolasyon
Înrudite33
RezumatUniversal 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.
ScholarGateSet de date
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  2. 2 Surse
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  1. v1
  2. 2 Surse
  3. PUBLISHED

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ScholarGateCompară metode: Universal Kriging · Inverse Distance Weighting. Preluat la 2026-06-19 de pe https://scholargate.app/ro/compare