ScholarGate
Asszisztens

Módszerek összehasonlítása

Tekintse át a kiválasztott módszereket egymás mellett; az eltérő sorok kiemelve jelennek meg.

Helyi univerzális kriging×Helyi Ordináris Kriging×
TudományterületTérbeli elemzésTérbeli elemzés
MódszercsaládRegression modelRegression model
Keletkezés éve1969/19971970s–1990s
MegalkotóMatheron, G. (trend/drift kriging); local neighborhood approach standard in geostatistical practiceJournel & Huijbregts; developed further by Goovaerts and Chiles & Delfiner
TípusSpatial interpolation modelGeostatistical interpolation (local/moving-window variant)
AlapműGoovaerts, P. (1997). Geostatistics for Natural Resources Evaluation. Oxford University Press. ISBN: 9780195115383Chiles, J.-P., & Delfiner, P. (1999). Geostatistics: Modeling Spatial Uncertainty. Wiley. ISBN: 978-0471083153
Alternatív neveklocal UK, local kriging with trend, local KED, local kriging with external driftmoving window kriging, local kriging, neighborhood kriging, LOK
Kapcsolódó55
ÖsszefoglalóLocal Universal Kriging is a geostatistical interpolation method that combines a spatially varying deterministic trend with a stochastic residual, estimated using only nearby observations within a defined search neighborhood. It generalizes local ordinary kriging by explicitly modeling and removing a polynomial or covariate-driven drift before interpolating the residual surface.Local Ordinary Kriging (LOK) is a geostatistical interpolation method that estimates values at unsampled locations using only a spatially defined moving neighborhood of nearby observations. By restricting each prediction to a local data window rather than the full dataset, LOK accommodates spatial non-stationarity, reduces computational cost, and often yields more accurate local predictions than global ordinary kriging.
ScholarGateAdatkészlet
  1. v1
  2. 2 Források
  3. PUBLISHED
  1. v1
  2. 2 Források
  3. PUBLISHED

Ugrás a kereséshez Diák letöltése

ScholarGateMódszerek összehasonlítása: Local Universal Kriging · Local Ordinary Kriging. Letöltve 2026-06-19, forrás: https://scholargate.app/hu/compare