Geostatistics for Natural Resources Evaluation
Oxford University Press, 1997 - Science - 483 pages
This text fulfills a need for an advanced-level work covering both the theory and application of geostatistics. It covers the most important areas of geostatistical methodology, introducing tools for description, quantitative modeling of spatial continuity, spatial prediction, and assessment of local uncertainty and stochastic simulation. It also details the theoretical background underlying most GSLIB programs. The tools are applied to an environmental data set, but the book includes a general presentation of algorithms intended for students and practitioners in such diverse fields as soil science, mining, petroleum, remote sensing, hydrogeology, and the environmental sciences.
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1.2 Distance km algorithms allows approach attribute average block bottom graph ccdf Cd concentration coefficient cokriging colocated combination component computed concentration ppm conditional Consider consists constraint contaminated continuous coregionalization correlation corresponding cost covariance critical cross covariance cross semivariogram datum defined depends direct distribution equal error estimates example experimental expression Figure function Gaussian given grid hence increases indicator inference Journel Kimmeridgian kriging linear linear model maps matrix mean measure metal ni(u normal score nugget effect ordinary kriging original pairs positive practice primary prior Prob probability proportion random range realizations relation resulting sample scattergram secondary semivariogram model shown shows simple simulated soft spatial standardized statistics study area threshold threshold values tion top graph transect transform trend uncertainty values variables variance vector weights z(ua zero
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