The Many Forms of Co-kriging: A Diversity of Multivariate Spatial Estimators
Peter A. Dowd, Eulogio Pardo‐Igúzquiza
Abstract
Abstract In this expository review paper, we show that co-kriging, a widely used geostatistical multivariate optimal linear estimator, has a diverse range of extensions that we have collected and illustrated to show the potential of this spatial interpolator. In the context of spatial stochastic processes, this paper covers scenarios including increasing the spatial resolution of a spatial variable (downscaling), solving inverse problems, estimating directional derivatives, and spatial interpolation taking boundary conditions into account. All these spatial interpolators are optimal linear estimators in the sense of being unbiased and minimising the variance of the estimation error.
Topics & Concepts
KrigingEstimatorMultivariate interpolationMultivariate statisticsInterpolation (computer graphics)Context (archaeology)Spatial dependenceMathematicsDownscalingStatisticsSpatial variabilityGeostatisticsSpatial contextual awarenessVariance (accounting)Computer scienceGeologyClimate changeBilinear interpolationArtificial intelligenceOceanographyAccountingMotion (physics)PaleontologyBusinessSoil Geostatistics and MappingLand Use and Ecosystem ServicesGeochemistry and Geologic Mapping