spatial statistics and geostatistics

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"Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice" - Professor Tao Cheng, University College London Focusing specifically on spatial statistics and including components for ArcGIS, R, SAS and WinBUGS, this book illustrates the use of basic spatial statistics and geostatistics, as well as the spatial filtering techniques used in all relevant programs and software. It explains and demonstrates techniques in: spatial sampling spatial autocorrelation local statistics spatial interpolation in two-dimensions advanced topics including Bayesian methods, Monte Carlo simulation, error and uncertainty. It is a systematic overview of the fundamental spatial statistical methods used by applied researchers in geography, environmental science, health and epidemiology, population and demography, and planning. A companion website includes digital R code for implementing the analyses in specific chapters and relevant data sets to run the R codes.

The Wiley Classics Library consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. Spatial statistics — analyzing spatial data through statistical models — has proven exceptionally versatile, encompassing problems ranging from the microscopic to the astronomic. However, for the scientist and engineer faced only with scattered and uneven treatments of the subject in the scientific literature, learning how to make practical use of spatial statistics in day-to-day analytical work is very difficult. Designed exclusively for scientists eager to tap into the enormous potential of this analytical tool and upgrade their range of technical skills, Statistics for Spatial Data is a comprehensive, single-source guide to both the theory and applied aspects of spatial statistical methods. The hard-cover edition was hailed by Mathematical Reviews as an "excellent book which will become a basic reference." This paper-back edition of the 1993 edition, is designed to meet the many technological challenges facing the scientist and engineer. Concentrating on the three areas of geostatistical data, lattice data, and point patterns, the book sheds light on the link between data and model, revealing how design, inference, and diagnostics are an outgrowth of that link. It then explores new methods to reveal just how spatial statistical models can be used to solve important problems in a host of areas in science and engineering. Discussion includes: Exploratory spatial data analysis Spectral theory for stationary processes Spatial scale Simulation methods for spatial processes Spatial bootstrapping Statistical image analysis and remote sensing Computational aspects of model fitting Application of models to disease mapping Designed to accommodate the practical needs of the professional, it features a unified and common notation for its subject as well as many detailed examples woven into the text, numerous illustrations (including graphs that illuminate the theory discussed) and over 1,000 references. Fully balancing theory with applications, Statistics for Spatial Data, Revised Edition is an exceptionally clear guide on making optimal use of one of the ascendant analytical tools of the decade, one that has begun to capture the imagination of professionals in biology, earth science, civil, electrical, and agricultural engineering, geography, epidemiology, and ecology.

Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area. It takes a unified, integrated approach to the material, providing cross-references among chapters. The handbook begins with a historical introduction detailing the evolution of the field. It then focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and spatial point patterns. The book also contains a section on space–time work as well as a section on important topics that build upon earlier chapters. By collecting the major work in the field in one source, along with including an extensive bibliography, this handbook will assist future research efforts. It deftly balances theory and application, strongly emphasizes modeling, and introduces many real data analysis examples.

This book is a collection of papers on spatial statistics for remote sensing. The book emerges from a study day that was organized in 1996 at the International Institute for Aerospace Survey and Earth Sciences, ITC, in Enschede, The Netherlands. It was by several means a memorable event. The beautiful new building, according to a design by the famous modern Dutch architect Max van Huet was just opened, and this workshop was the first to take place there. Of course, much went wrong during the workshop, in particular as the newest electronic equipment regularly failed. But the workshop attrackted more than hundred attendants, and was generally well received. The results of the workshop have been published in Stein et al. (1998). The aim of the workshop was to address issues of spatial statistics for remote sensing. The ITC has a long history on collecting and analyzing satellite and other remote sensing data, but its involvement into spatial statistics is of a more recent date. Uncertainties in remote sensing images and the large amounts of data in many spectral bands are now considered to be of such an impact that it requires a separate approach from a statistical point of view. To quote from the justification of the study day, we read: Modern communication means such as remote sensing require an advanced use of collected data. Satellites collect data with different resolution on different spectral bands.

This volume compiles geostatistical and spatial autoregressive data analyses involving georeferenced socioeconomic, natural resources, agricultural, pollution, and epidemiological variables. Benchmark analyses are followed by analyses of readily available data sets, emphasizing parallels between geostatistical and spatial autoregressive findings. Both SAS and SPSS code are presented for implementation purposes. This informative casebook will serve geographers, regional scientists, applied spatial statisticians, and spatial scientists from across disciplines.

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.

The Handbook is written for academics, researchers, practitioners and advanced graduate students. It has been designed to be read by those new or starting out in the field of spatial analysis as well as by those who are already familiar with the field. The chapters have been written in such a way that readers who are new to the field will gain important overview and insight. At the same time, those readers who are already practitioners in the field will gain through the advanced and/or updated tools and new materials and state-of-the-art developments included. This volume provides an accounting of the diversity of current and emergent approaches, not available elsewhere despite the many excellent journals and te- books that exist. Most of the chapters are original, some few are reprints from the Journal of Geographical Systems, Geographical Analysis, The Review of Regional Studies and Letters of Spatial and Resource Sciences. We let our contributors - velop, from their particular perspective and insights, their own strategies for m- ping the part of terrain for which they were responsible. As the chapters were submitted, we became the first consumers of the project we had initiated. We gained from depth, breadth and distinctiveness of our contributors’ insights and, in particular, the presence of links between them.

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.

Introduction to Geostatistics presents practical techniques for engineers and applied geophysicists who routinely encounter interpolation and estimation problems when analyzing data from field observations. Requiring no background in statistics, and with a unique approach that synthesizes classic and geostatistical methods, this book presents linear estimation methods for practitioners and advanced students. Well illustrated with exercises and worked examples, taken from hydrogeology Introduction to Geostatistics is suitable for graduate-level courses in earth sciences and environmental engineering, and also for self-study.

This unique book presents a learn-by-doing introduction togeostatistics. Geostatistics provides the essential numerical tools foraddressing research problems that are encountered in fields ofstudy such as geology, engineering, and the earth sciences.Illustrating key methods through both theoretical and practicalexercises, Solved Problems in Geostatistics is a valuableand well-organized collection of worked-out problems that allow thereader to master the statistical techniques for modeling data inthe geological sciences. The book's scope of coverage begins with the elements fromstatistics and probability that form the foundation of mostgeostatistical methodologies, such as declustering, debiasingmethods, and Monte Carlo simulation. Next, the authors delve intothree fundamental areas in conventional geostatistics: covarianceand variogram functions; kriging; and Gaussian simulation. Finally,special topics are introduced through problems involving utilitytheory, loss functions, and multiple-point geostatistics. Each topic is treated in the same clearly organized format.First, an objective presents the main concepts that will beestablished in the section. Next, the background and assumptionsare outlined, supplying the comprehensive foundation that isnecessary to begin work on the problem. A solution plandemonstrates the steps and considerations that have to be takenwhen working with the exercise, and the solution allows the readerto check their work. Finally, a remarks section highlights theoverarching principles and noteworthy aspects of the problem. Additional exercises are available via a related Web site, whichalso includes data related to the book problems and softwareprograms that facilitate their resolution. Enforcing a trulyhands-on approach to the topic, Solved Problems inGeostatistics is an indispensable supplement for courses ongeostatistics and spatial statistics a the upper-undergraduate andgraduate levels.It also serves as an applied reference forpracticing professionals in the geosciences.

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