Geostatistics for Engineers and Earth Scientists (Hardcover)

by Ricardo A. Olea (Author) "Geostatistics can be regarded as a collection of numerical techniques that deal with the characterization of spatial attributes, employing primarily random models in a manner..." (more)
Key Phrases: regionalized classification, vectorial random function, linear coregionalization model, Characterization of One Attribute, Proof From Theorem, Hodgeman County (more...)

Editorial Reviews

Review
`This book ... is one of the best introductions to geostatistics. It is a perfect balance between theory and methodological considerations. ... Even the more experienced geostatisticians will read it with great pleasure and will find for it a very special place on their bookshelf. It is the kind of book that you enjoy recommending to anyone who wants a good starting point in a field. ... I very stronly recommend this book to anyone who wants to have an introductive, consistent and unbiased view of geostatistics, a discipline that urgently needs young and enthusiastic scientists with a fresh view of the problems. In this sense, this book should help us a lot, at least as much as it will help them.' P. Bogaert in Stochastic Environmental Research and Risk Assessment, 14 (2000) 'This book should be seriously considered for adoption in a graduate level course on geostatistics. Moreover, this book would make a valuable addition to any library on spatial analysis.' Mathematical Geology, July (2002)

Product Description
Engineers and earth scientists are increasingly interested in quantitative methods for the analysis, interpretation, and modeling of data that imperfectly describe natural processes or attributes measured at geographical locations. Inference from imperfect knowledge is the realm of classical statistics. In the case of many natural phenomena, auto- and cross- correlation preclude the use of classical statistics. The appropriate choice in such circumstances is geostatistics, a collection of numerical techniques for the characterization of spatial attributes similar to the treatment in time series analysis of auto-correlated temporal data. As in time series analysis, most geostatistical techniques employ random variables to model the uncertainty that goes with the assessments. The applicability of the methods is not limited by the physical nature of the attributes. Geostatistics for Engineers and Earth Scientists presents a concise introduction to geostatistics with an emphasis on detailed explanations of methods that are parsimonious, nonredundant, and through the test of time have proved to work satisfactorily for a variety of attributes and sampling schemes. Most of these methods are various forms of kriging and stochastic simulation. The presentation follows a modular approach making each chapter as self-contained as possible, thereby allowing for reading of individual chapters, reducing excessive cross-referencing to previous results and offering possibilities for reviewing similar derivations under slightly different circumstances. Guidelines and rules are offered wherever possible to help choose from among alternative methods and to select parameters, thus relieving the user from making subjective calls based on an experience that has yet to be acquired. Geostatistics for Engineers and Earth Scientists is intended to assist in the formal teaching of geostatistics or as a self tutorial for anybody who is motivated to employ geostatistics for sampling design, data analysis, or natural resource characterization. Real data sets are used to illustrate the application of the methodology.

Product Details

• Hardcover: 324 pages
• Publisher: Springer; 1st edition (May 31, 1999)
• Language: English
• ISBN-10: 0792385233
• ISBN-13: 978-0792385233
• Product Dimensions: 9.3 x 6.2 x 0.9 inches
• Shipping Weight: 1.2 pounds (View shipping rates and policies)
• Average Customer Review: 4.0 out of 5 stars See all reviews (4 customer reviews)
• Amazon.com Sales Rank: #973,619 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

10 of 11 people found the following review helpful:

5.0 out of 5 stars From "Stochastic Environmental Research and Risk Assessment," 14(3)207-209, October 3, 2000

By	Patrick Bogaert (Louvain-la-Neuve, Belgium) - See all my reviews

One could wonder how a new textbook in geostatistics would have a chance to offer something new and fresh to the reader, when there are so many of them already available on the market. The answer is contained in a sentence that could not be better and more clearly summarized than by the author himself, in the introductory chapter: "Derivations in mathematical books are unnecessarily general, resulting in a complexity that tends to intimidate the uninitiated, while explanations in geostatistical books are cryptically short--to the point that most readers end up taking the derivations for granted."

This single sentence is also the philosophy of this book. By keeping a constant link and perfect balance between theoretical and methodological concerns, the book allows the novice reader to discover step by step the exciting realm of geostatistics and its applications. As explained by the author, this textbook is the result of a long teaching experience to engineering students at the graduate level. After reading this book, I have to say that I wish I could have had the chance to be one of his students when I was struggling myself with theory as a Ph.D. student a few years ago.

A requirement for reading the book is a college-level knowledge in matrix algebra, probability, and statistics. I have found that in spite of its obviousness, this clarification is sometimes lacking in other introductory books, which tend to present the material in such a way the reader could wrongly believe that he or she will be able to grasp the basics and even the more advanced results without the necessity of having a basic command of the disciplines (probability and statistics) that underlie geostatistics. The author also emphasizes that "many of the suggestions of my colleagues were incorporated into the final text, but I reserve the right, and assume the blame, for disagreeing in a few instances." This sentence shows us that beyond the various streams that exist in the field, the author had in mind the concern of presenting a view of the field as objective as possible to the newcomer, which is a very responsible attitude.

The book includes 14 chapters. Each chapter is organized in a very clear fashion, by making distinctions between what is a definition, lemma, theorem, corollary, assumption, or algorithm. This helps the reader avoid confusion about a pure theoretical property and widely accepted methodological ways of having the job done. A proof for each lemma, theorem, and corollary, as direct as possible, is provided each time and allows the curious reader to discover why things are the way they are. This theoretical presentation is accompanied in many places by practical guidelines and discussions that help the reader to make the step from theory to practice. Numerous, very practical, exercises are proposed, as well as commented and illustrated solutions. Only the most classical techniques are presented, allowing the reader to focus on the essentials, rather than being overwhelmed by numerous variations on the same topic and the unavoidable and often confusing discussion about advantages and disadvantages of each of them. Adequate additional references are provided for the reader who wants to go further herself or himself.

I would conclude by saying that this book, in my opinion, is one of the best introductions to geostatistics that I have ever read. It is a perfect balance between theory and methodological considerations. The presentation of the various techniques is made with a permanent concern for the comprehension of the underlying theory, without neglecting the illustrative part that helps the reader to fully understand the implications of the developments. It is concise and yet complete enough for helping the newcomer to find his or her way in the meanders of this rapidly evolving discipline. I am sure that even the more experienced geostatisticians will read it with great pleasure and will find for it a very special place on their bookshelf. It is the kind of book that you enjoy recommending to anyone who wants a good starting point in a field. I will personally use it as reference book for my students. In summary, I very strongly recommend this book to anyone who wants to have an introductory, consistent, and unbiased view of geostatistics.

5.0 out of 5 stars great refeence for student and professional, July 3, 2008

By	Donald R. Stark (Denver, CO) - See all my reviews (REAL NAME)

Got this for a GIS class. Great reference book for both a student and professional wanting to know about geo-statistics and kridging.

1 of 2 people found the following review helpful:

5.0 out of 5 stars Good reference for Geostat, February 22, 2004

By	L. D. Teran - See all my reviews (REAL NAME)

I strongly recommend this book for reference and self study. It contains tons of useful definitions, theorems,lemmas, etc.., all with proofs. The algorithms are presented in a very clear and detailed way. The assumptions are stated clearly. It helps a lot with the math and derivations.