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This book describes statistical methods suitable for analyzing variation in soil and for relating soil to its environment. The authors stress sound sampling technique and show how to use the results for estimation, prediction, and efficient design. They show how classification can enhance the utility of survey data and lead to economies in sampling. Optimal methods for creating classification are described, and alternative multivariate methods are set forth for identifying relations such as principal component and co-ordinate analysis. The book expands and revises the author's Quantitative and Numerical Methods in Soil Classification and Survey. It includes information on regression, as used in both statistics and natural science. Three new chapters devoted to geostatistics introduce regionalized variable theory, and cover such applications as the variogram, its modelling, kriging, and isorithmic mapping. As with the first edition, the book stresses the full quantitative survey of land resources, measurement, and estimation. Many simple illustrations and tables are included to clarify the text.
This book investigates the application of statistical methodologies to analyze soil variation and its relationship with the surrounding environment. Authors M. A. Oliver and R. Webster leverage their extensive expertise in soil science and quantitative analysis to provide a framework for sound sampling techniques. The text argues that rigorous statistical design is essential for accurate estimation, prediction, and the efficient management of land resource surveys.
What You Will Find
Experts recognize this work as a foundational text for professionals and students engaged in quantitative soil survey and land resource management. Readers frequently note the technical density of the prose, which serves as a rigorous reference for applying geostatistics to environmental data.
Page Count:
328
Publication Date:
1990-12-13
Publisher:
Oxford University Press
ISBN-10:
0198233167
ISBN-13:
9780198233169
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