ScholarGate
アシスタント

手法を比較

選択した手法を並べて確認できます。異なる行はハイライト表示されます。

ユニバーサル・クリーギング(トレンド付きクリーギング)×逆距離加重法 (IDW)×
分野空間分析空間分析
系統Regression modelRegression model
提唱年19691968
提唱者Georges MatheronDonald Shepard
種類Geostatistical interpolation with spatial trendDeterministic spatial interpolation
原典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 ↗
別名kriging with a trend, kriging with drift, trend kriging, evrensel krigingIDW, inverse distance interpolation, Shepard's method, ters mesafe ağırlıklı enterpolasyon
関連33
概要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.
ScholarGateデータセット
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 2 出典
  3. PUBLISHED

検索へ スライドをダウンロード

ScholarGate手法を比較: Universal Kriging · Inverse Distance Weighting. 2026-06-19に以下より取得 https://scholargate.app/ja/compare