Collecting Spatial Data: Optimum Design of Experiments for Random Fields (Contributions to Statistics) [Paperback]

W. G. Muller (Author)

Book Description

ISBN-10: 3790811343 | ISBN-13: 978-3790811346 | Publication Date: January 1998

This text is concerned with the statistical theory for locating spatial sensors. It bridges the gap between spatial statistics and optimum design theory. After introductions to those two fields the topics of exploratory designs and designs for spatial trend and variogram estimation are treated. A methodology, so-called approximate information matrices, are employed to cope with the problem of correlated observations. A great number of relevant references are collected and put into a common perspective. The theoretical investigations are accompanied by a practical example, the redesign of an Upper-Austrian air pollution monitoring network. The reader will find respective theory and recommendations on how to plan efficiently a specific-purpose spatial monitoring network.

Editorial Reviews

Review

From the reviews of the third edition: "Collecting Spatial Data signifies … the state of the art of the design of spatial networks. … the monograph is well focused on the important problem of spatial sampling. … The book will continue to be a stalwart reference for practitioners in the field of spatial estimation and a thorough introduction for graduate students in the field. This third edition nicely fulfills the aim … of providing an overview of classical and recent methods for the efficient collection of spatial data." (Michael Manton, Eos, Vol. 89 (15), 2008) --This text refers to the Hardcover edition.

From the Back Cover

The book is concerned with the statistical theory for locating spatial sensors. It bridges the gap between spatial statistics and optimum design theory. After introductions to those two fields the topics of exploratory designs and designs for spatial trend and variogram estimation are treated. Special attention is devoted to describing new methodologies to cope with the problem of correlated observations. A great number of relevant references are collected and put into a common perspective. The theoretical investigations are accompanied by a practical example, the redesign of an Upper-Austrian air pollution monitoring network. A reader should be able to find respective theory and recommendations on how to efficiently plan a specific purpose spatial monitoring network. The third edition takes into account the rapid development in the area of spatial statistics by including new relevant research and references. The revised edition contains additional material on design for detecting spatial dependence and for estimating parametrized covariance functions.   --This text refers to the Hardcover edition.

Product Details

• Paperback: 186 pages
• Publisher: Physica-Verlag (January 1998)
• Language: English
• ISBN-10: 3790811343
• ISBN-13: 978-3790811346
• Product Dimensions: 9.2 x 6.2 x 0.5 inches
• Shipping Weight: 10.4 ounces (View shipping rates and policies)
• Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #10,199,188 in Books (See Top 100 in Books)

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Most Helpful Customer Reviews

4 of 5 people found the following review helpful:

4.0 out of 5 stars First book on spatial design, April 5, 2001

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Random Thoughts (Maryland) - See all my reviews

This review is from: Collecting Spatial Data: Optimum Design of Experiments for Random Fields (Contributions to Statistics) (Paperback)

Spatial statistics is an important subject, and there are excellent books such as Ripley, Cressie's books. However, very little work has been done on how to collect spatial data, though experimental design is an old but important subject in Statistics. This book, now in its second edition, makes an excellent start in this emerging area. This reviewer, fortunately, has the chance to participate in a multinational weather experiment in which one of the goals is to collect additional spatial data for improving existing data network and for improving short-time-scale and mesoscale weather forecast. This led to our study of adaptive design for spatial dynamical systems and spatial fields, leading to a 1999 paper on J. of Atmospheric Sciences and a book Chapter in Studies in Atmospheric Sciences published by Springer in 2000. Now, adaptive spatial design, or targeted observations, is an very hot area in meteorology, and many papers have published in meteorology dealing with various aspects of applications. There are good economic reasons also for doing adaptive design, though practical impacts of this approach need to be justified also. After making this unnecessary detour, what do I think of this book? Well, I think it's an excellent supplementary book for a spatial statistics course. This book only covers the classic aspects of spatial design, namely a frequentist approach to static design for standard spatial estimation and prediction, with applications such as in designing monitoring stations. By combining with our more recent work optimal design using Bayesian methods, you probably get a very good coverage of statistical design for spatial or space-time fields, an area which I foresee more developments in the future.