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역거리 가중치법 (IDW)×보편 크리깅 (추세가 있는 크리깅)×
분야공간분석공간분석
계열Regression modelRegression model
기원 연도19681969
창시자Donald ShepardGeorges Matheron
유형Deterministic spatial interpolationGeostatistical interpolation with spatial trend
원전Shepard, 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 ↗
별칭IDW, inverse distance interpolation, Shepard's method, ters mesafe ağırlıklı enterpolasyonkriging with a trend, kriging with drift, trend kriging, evrensel kriging
관련33
요약Inverse 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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ScholarGate방법 비교: Inverse Distance Weighting · Universal Kriging. 2026-06-19에 다음에서 검색함: https://scholargate.app/ko/compare