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On the relationship between kriging and state estimation
Author(s) -
Chirlin Gary R.,
Wood Eric F.
Publication year - 1982
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr018i002p00432
Subject(s) - kriging , interpolation (computer graphics) , multivariate interpolation , process (computing) , estimation , variogram , geostatistics , nearest neighbor interpolation , computer science , state (computer science) , noise (video) , mathematics , algorithm , mathematical optimization , statistics , spatial variability , bilinear interpolation , artificial intelligence , engineering , motion (physics) , systems engineering , image (mathematics) , operating system
Interpolation of sampled random spatial processes is of interest to hydrologists. The interpolation task requires the determination of an underlying process that may be confounded by both process noise and data measurement error. One approach that has appeared in the hydrologic literature is universal kriging. Universal kriging interpolates a discrete stationary spatial process obtained by polynomial filtering through spatial differencing of the original nonstationary process. The interpolation procedure of kriging is presented within the more general framework of state estimation. The paper analyzes the assumptions and limitations of kriging within state estimation and discusses some of the concerns of practitioners which have arisen in recent papers.