Geostatistics for Natural Resources Evaluation [Hardcover]

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.

1. Introduction
2. Exploratory Data Analysis
3. The Random Function Model
4. Inference and Modeling
5. Local Estimation: Accounting for a Single Attribute
6. Local Estimation: Accounting for Secondary Information
7. Assessment of Local Uncertainty
8. Assessment of Spatial Uncertainty
9. Summary

Every decade or so, as knowledge about geostatistical concepts has developed and evolved, a book has appeared that has seemed to uniquely define the discipline at that point in time. This is one of those books, providing a remarkable synthesis of all that this field of study is about and has become over the last 10 years. It is clearly the best overall presentation of geostatistical theory and methodology currently available today. As a teaching resource, the book provides comprehensive coverage of all the major geostatistical topics of both current and historical interest. This book is unmistakably the leader in its field today, and it will likely be so throughout most of the decade to come. Anyone seriously engaged in the development and practice of geostatistical methodology will want to have a copy close at hand. Goovaerts is to be commended for his tireless efforts in producing a volume that should stand the test of time. --Timothy Coburn, Technometricsl“p