Value of Information in the Earth Sciences: Integrating Spatial Modeling and Decision Analysis [Hardcover]

This book presents a unified framework for assessing the value of potential data-gathering schemes, with a focus on the Earth sciences.This book presents a unified framework for assessing the value of potential data gathering schemes by integrating spatial modelling and decision analysis, with a focus on the Earth sciences. Real datasets and MATLAB codes are provided online, making this an invaluable reference for students, researchers, and industry professionals.This book presents a unified framework for assessing the value of potential data gathering schemes by integrating spatial modelling and decision analysis, with a focus on the Earth sciences. Real datasets and MATLAB codes are provided online, making this an invaluable reference for students, researchers, and industry professionals.Gathering the right kind and the right amount of information is crucial for any decision-making process. This book presents a unified framework for assessing the value of potential data gathering schemes by integrating spatial modelling and decision analysis, with a focus on the Earth sciences. The authors discuss the value of imperfect versus perfect information, and the value of total versus partial information, where only subsets of the data are acquired. Concepts are illustrated using a suite of quantitative tools from decision analysis, such as decision trees and influence diagrams, as well as models for continuous and discrete dependent spatial variables, including Bayesian networks, Markov random fields, Gaussian processes, and multiple-point geostatistics. Unique in scope, this book is of interest to students, researchers and industry professionals in the Earth and environmental sciences, who use applied statistics and decision analysis techniques, and particularly to those working in petroleum, mining, and environmental geoscience.Preface; 1. Introduction; 2. Statistical models and methods; 3. Decision analysis; 4. Spatial modeling; 5. Value of information in spatial decilS(