D.D. Sarma: Geostatistics with Applications in Earth Sciences, 2nd edn.
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D.D. Sarma: Geostatistics with Applications in Earth Sciences, 2nd edn. Springer, Dordrecht, and Capital Publishing Company, New Delhi, 2009, xvii + 205 pages, hardback, ISBN 978-1-4020-9379-1, Eur 79.95, CHF124.50, US$99.00, £72.00 R. Webster Received: 10 November 2009 / Accepted: 10 November 2009 / Published online: 27 November 2009 © International Association for Mathematical Geosciences 2009
The first edition of Geostatistics with Applications in Earth Sciences appeared in 2002, and in reviewing it in Mathematical Geology, volume 36, pages 987–989, T.C. Coburn wrote, ‘. . . not a particularly remarkable book, but it is certainly not a bad one either. It is just that it is somewhat minimalistic—even sparse—in nature . . . ’. The second edition has been expanded, but ‘minimalistic’ still aptly summarizes its treatment of the subject. The new material comprises additions to Chapter 1 on sampling, a section on Monte Carlo simulation in Chapter 2, description of ‘binning’ to compute experimental variograms, which should never have been overlooked earlier, and a short new chapter entitled ‘Introduction to Advanced Geostatistics’. I can agree with Coburn that the book is not a bad one; it has its merits. I cannot agree with the first comment; in my view the book is remarkable in several particulars, not all praiseworthy; I return to them below. The author sets off at a gentle pace on the basic ideas of populations and samples, of summary statistics and their presentation as histograms and pie charts. The pace accelerates with correlation and regression, frequency distributions and confidence, transformations, and significance tests. Chi-square and its distribution are introduced, mainly to test how well other distributions fit the observed distributions in sample data. Tables list counts from which you can see how to do the computations. The text gathers pace even faster in Chapter 4, entitled ‘Stochastic Modelling (Time Series Analysis) and Forecasting’. This is advanced stuff, and not what you expect to find in a book on geostatistics. The motivation for it seems to be the desire to predict the concentrations of metal in a borehole ahead of the drill bit. Chapter 5 takes us into mainstream geostatistics. There we encounter the variogram and its various characteristics, with emphasis on the spherical model. The next R. Webster () Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ, UK e-mail: [email protected]
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Math Geosci (2010) 42: 355–357
two chapters pursue the theme with regularization, grade tonnage computations, variance–volume relations, Krige’s relation, the extension variance and estimation variance, matters of especial interest to miners. Kriging is the subject of Chapter 8. The ordinary kriging system is developed step by step in full with its solution leading to the kriging prediction and its variance. The changes needed for simple kriging follow. The chapter includes worked examples so that you can see the arithmetic. Chapter 9 introduces three advanced topics. Universal kriging is an
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