Author: Edward H. Isaaks Publisher: ISBN: Category : Geology Languages : en Pages : 561
Book Description
Univariate description. Bivariate description. Spatial description. Data sets. Estimation. Random function models. Global estimation. Point estimation. Ordinary kriging. Block kriging. Search strategy. Cross validation. Cokriging. Estimating a distribution. Change of support. Assessing uncertainty. Final thoughts.
Author: Nicolas Remy Publisher: Cambridge University Press ISBN: 1139473468 Category : Science Languages : en Pages : 302
Book Description
The Stanford Geostatistical Modeling Software (SGeMS) is an open-source computer package for solving problems involving spatially related variables. It provides geostatistics practitioners with a user-friendly interface, an interactive 3-D visualization, and a wide selection of algorithms. This practical book provides a step-by-step guide to using SGeMS algorithms. It explains the underlying theory, demonstrates their implementation, discusses their potential limitations, and helps the user make an informed decision about the choice of one algorithm over another. Users can complete complex tasks using the embedded scripting language, and new algorithms can be developed and integrated through the SGeMS plug-in mechanism. SGeMS was the first software to provide algorithms for multiple-point statistics, and the book presents a discussion of the corresponding theory and applications. Incorporating the full SGeMS software (now available from www.cambridge.org/9781107403246), this book is a useful user-guide for Earth Science graduates and researchers, as well as practitioners of environmental mining and petroleum engineering.
Author: Pierre Goovaerts Publisher: Oxford University Press, USA ISBN: 9780195115383 Category : Mathematics Languages : en Pages : 502
Book Description
This text provides an advanced introduction to the theory and applications of geostatistics, including tools for description, modeling spatial continuity, spatial prediction, assessment of local uncertainty, and stochastic simulation.
Author: Marcel Antonio Arcari Bassani Publisher: Springer Nature ISBN: 3030801934 Category : Science Languages : en Pages : 75
Book Description
This book explains the integration of data of different support in Geostatistics. There is a common misconception in the mining industry that the data used for estimation/simulation should have the same size or support. However, Geostatistics provides the tools to integrate several types of information that may have different support. This book aims to explain these geostatistical tools and provides several examples of applications. The book is directed for a broad audience, including engineers, geologists, and students in the area of Geostatistics.
Author: Richard Webster Publisher: John Wiley & Sons ISBN: 9780470517260 Category : Mathematics Languages : en Pages : 330
Book Description
Geostatistics is essential for environmental scientists. Weather and climate vary from place to place, soil varies at every scale at which it is examined, and even man-made attributes – such as the distribution of pollution – vary. The techniques used in geostatistics are ideally suited to the needs of environmental scientists, who use them to make the best of sparse data for prediction, and top plan future surveys when resources are limited. Geostatistical technology has advanced much in the last few years and many of these developments are being incorporated into the practitioner’s repertoire. This second edition describes these techniques for environmental scientists. Topics such as stochastic simulation, sampling, data screening, spatial covariances, the variogram and its modeling, and spatial prediction by kriging are described in rich detail. At each stage the underlying theory is fully explained, and the rationale behind the choices given, allowing the reader to appreciate the assumptions and constraints involved.
Author: P. K. Kitanidis Publisher: Cambridge University Press ISBN: 9780521587471 Category : Science Languages : en Pages : 276
Book Description
Engineers and applied geophysicists routinely encounter interpolation and estimation problems when analysing data from field observations. Introduction to Geostatistics presents practical techniques for the estimation of spatial functions from sparse data. The author's unique approach is a synthesis of classic and geostatistical methods with a focus on the most practical linear minimum-variance estimation methods, and includes suggestions on how to test and extend the applicability of such methods. The author includes many useful methods (often not covered in other geostatistics books) such as estimating variogram parameters, evaluating the need for a variable mean, parameter estimation and model testing in complex cases (e.g. anisotropy, variable mean, and multiple variables), and using information from deterministic mathematical models. Well illustrated with exercises and worked examples taken from hydrogeology, Introduction to Geostatistics assumes no background in statistics and is suitable for graduate-level courses in earth sciences, hydrology, and environmental engineering, and also for self-study.
Author: Peter J. Diggle Publisher: CRC Press ISBN: 1351743260 Category : Mathematics Languages : en Pages : 211
Book Description
Model-based Geostatistics for Global Public Health: Methods and Applications provides an introductory account of model-based geostatistics, its implementation in open-source software and its application in public health research. In the public health problems that are the focus of this book, the authors describe and explain the pattern of spatial variation in a health outcome or exposure measurement of interest. Model-based geostatistics uses explicit probability models and established principles of statistical inference to address questions of this kind. Features: Presents state-of-the-art methods in model-based geostatistics. Discusses the application these methods some of the most challenging global public health problems including disease mapping, exposure mapping and environmental epidemiology. Describes exploratory methods for analysing geostatistical data, including: diagnostic checking of residuals standard linear and generalized linear models; variogram analysis; Gaussian process models and geostatistical design issues. Includes a range of more complex geostatistical problems where research is ongoing. All of the results in the book are reproducible using publicly available R code and data-sets, as well as a dedicated R package. This book has been written to be accessible not only to statisticians but also to students and researchers in the public health sciences. The Authors Peter Diggle is Distinguished University Professor of Statistics in the Faculty of Health and Medicine, Lancaster University. He also holds honorary positions at the Johns Hopkins University School of Public Health, Columbia University International Research Institute for Climate and Society, and Yale University School of Public Health. His research involves the development of statistical methods for analyzing spatial and longitudinal data and their applications in the biomedical and health sciences. Dr Emanuele Giorgi is a Lecturer in Biostatistics and member of the CHICAS research group at Lancaster University, where he formerly obtained a PhD in Statistics and Epidemiology in 2015. His research interests involve the development of novel geostatistical methods for disease mapping, with a special focus on malaria and other tropical diseases. In 2018, Dr Giorgi was awarded the Royal Statistical Society Research Prize "for outstanding published contribution at the interface of statistics and epidemiology." He is also the lead developer of PrevMap, an R package where all the methodology found in this book has been implemented.
Author: Hans Wackernagel Publisher: Springer Science & Business Media ISBN: 3662035502 Category : Science Languages : en Pages : 259
Book Description
An introduction to geostatistics stressing the multivariate aspects for scientists, engineers and statisticians. The book presents a brief review of statistical concepts, a detailed introduction to linear geostatistics, and an account of three basic methods of multivariate analysis. Applications from very different areas of science, as well as exercises with solutions, are provided to help convey the general ideas. In this second edition, the chapters regarding normal kriging and cokriging have been restructured and the section on non-stationary geostatistics has been entirely rewritten.
Author: Raimon Tolosana-Delgado Publisher: Springer Nature ISBN: 303082568X Category : Mathematics Languages : en Pages : 275
Book Description
This book provides a guided approach to the geostatistical modelling of compositional spatial data. These data are data in proportions, percentages or concentrations distributed in space which exhibit spatial correlation. The book can be divided into four blocks. The first block sets the framework and provides some background on compositional data analysis. Block two introduces compositional exploratory tools for both non-spatial and spatial aspects. Block three covers all necessary facets of multivariate spatial prediction for compositional data: variogram modelling, cokriging and validation. Finally, block four details strategies for simulation of compositional data, including transformations to multivariate normality, Gaussian cosimulation, multipoint simulation of compositional data, and common postprocessing techniques, valid for both Gaussian and multipoint methods. All methods are illustrated via applications to two types of data sets: one a large-scale geochemical survey, comprised of a full suite of geochemical variables, and the other from a mining context, where only the elements of greatest importance are considered. R codes are included for all aspects of the methodology, encapsulated in the R package "gmGeostats", available in CRAN.
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Author: Edward H. Isaaks
Author: Nicolas Remy
Author: Pierre Goovaerts
Author: Marcel Antonio Arcari Bassani
Author: Richard Webster
Author: Mohan Kelkar
Author: P. K. Kitanidis
Author: Peter J. Diggle
Author: Hans Wackernagel
Author: Raimon Tolosana-Delgado