kriging


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kri·ging

(krī'jing),
A method first used in the earth sciences to smooth data from spatially scattered point measurements, used in geographic epidemiology.
[D. G. Krige, South African engineer]

kri·ging

(krī'jing)
A method first used in the earth sciences to smooth data from spatially scattered point measurements, used in geographic epidemiology.
[D. G. Krige, South African engineer]
References in periodicals archive ?
Laermans, "Performance study of gradient-enhanced Kriging," Engineering with Computers, vol.
Existing studies show that the Kriging method is the best way to estimate the parameters of the radio environment map.
The pointwise SWI values are then spatially interpolated in GIS environment using the ordinary kriging method and ArcGIS 10.2 software to find out the areal extent of drought in the study area.
The other method of interpolation used to generate drought intensity surface was Inverse Distance Weighted (IDW) and Kriging with Gaussian semivariogram (Figure-2 and 3).
We used a land-use, mixed-effects regression model developed with readily available data (air quality and meteorological monitoring data, road networks information, latitude) and two spatiotemporal interpolation models: a) a combined land-use BME model incorporating both [O.sub.3] monitoring station data and the land-use mixed model outputs (BMELUR), and b) a kriging method based only on available data from [O.sub.3] monitoring stations (BME kriging).
The most commonly used methods of interpolation in geographic information systems (GIS) are inverse distance weight (IDW) (Buchanan and Triantafilis, 2009; Sun et al., 2009), spline (Varouchakis and Hristopulos, 2013; Buchanan and Triantafilis, 2009) and Kriging (Pokhrel et al., 2013; Sun et al, 2009; Yang et al., 2008).
This paper presents an effective optimization method based on Kriging metamodel.
Kriging is a geostatistical estimation method which can be considered as the best unbiased estimator.
Co-Kriging is a multivariate enhancement to the geostatistical method of Kriging [7], that attempts to build an approximation of a function that is expensive to evaluate, through coupling cheap low fidelity data (auxiliary) with a small amount of high fidelity data (primary) [13].
Univariate kriging methods including ordinary kriging and universal kriging have been widely applied to environmental science, natural resources, remote sensing, and GIS.
Keywords: Water quality, Water quality index, Effective weights, Empirical bayesian kriging, Ordinary kriging, Principal component analysis.