Probabilistic integration of geo-information

Thomas Mejer Hansen, Knud Skou Cordua, Andrea Zunino, Klaus Mosegaard

12 Citationer (Scopus)
82 Downloads (Pure)

Abstract

The problem of inferring information about the Earth can be described as a data integration problem, where the solutions a probability distribution that combines all available information. This chapter presents the methods for probabilistic characterization of different kinds of geo-information. Then a number of methods that allow inferring information from the probability distribution that combines all available information are discussed. Straight forward application of classic sampling algorithms such as the rejection sampler and the Metropolis algorithm will in most cases lead to computationally intractable problems. A wide range of statistical methods, providing varying degrees of information content, are currently available that can be used with the extended Metropolis algorithm and that allow characterization of probability distributions describing quite complex and geologically realistic spatial features. These methods allow building statistical models that assume, in principle, a lot more than is typically known.

OriginalsprogEngelsk
TitelIntegrated imaging of the earth : theory and applications
ForlagWiley
Publikationsdato1 apr. 2016
Sider93-116
Kapitel6
ISBN (Trykt)978-1-118-92905-6
DOI
StatusUdgivet - 1 apr. 2016

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