ScholarGate
Asistenti

Krahasoni metodat

Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.

Krigimi Universal Lokal×Krigingu i Zakonshëm Lokal×
FushaAnaliza hapësinoreAnaliza hapësinore
FamiljaRegression modelRegression model
Viti i origjinës1969/19971970s–1990s
KrijuesiMatheron, G. (trend/drift kriging); local neighborhood approach standard in geostatistical practiceJournel & Huijbregts; developed further by Goovaerts and Chiles & Delfiner
LlojiSpatial interpolation modelGeostatistical interpolation (local/moving-window variant)
Burimi themeluesGoovaerts, 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
Emërtime të tjeralocal UK, local kriging with trend, local KED, local kriging with external driftmoving window kriging, local kriging, neighborhood kriging, LOK
Të lidhura55
PërmbledhjaLocal 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.
ScholarGateSeti i të dhënave
  1. v1
  2. 2 Burimet
  3. PUBLISHED
  1. v1
  2. 2 Burimet
  3. PUBLISHED

Shko te kërkimi Shkarko diapozitivat

ScholarGateKrahasoni metodat: Local Universal Kriging · Local Ordinary Kriging. Marrë më 2026-06-19 nga https://scholargate.app/sq/compare