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Geostatistics for natural resources evaluation.

By: Language: English Series: Applied geostatisticsPublication details: United States of America Oxford University Press 1997Description: xiv, 483 páginas; table, figures, grafico; 24 cm x 16.5 cmISBN:
  • 9780195115383
Subject(s): DDC classification:
  • 310 G659
Contents:
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
Summary: 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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Holdings
Item type Current library Call number Copy number Status Date due Barcode
Libros Libros CIBESPAM-MFL 310 / G659 (Browse shelf(Opens below)) Ej: 1 Available 006005
Libros Libros CIBESPAM-MFL 310 / G659 (Browse shelf(Opens below)) Ej: 2 Available 006006

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

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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