Geostatistics for Natural Resources Evaluation (Applied Geostatistics Series) | 
 enlarge | Author: Pierre Goovaerts
Publisher: Oxford University Press, USA
Category: Book
List Price: $136.95
Buy New: $108.88
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New (13) Used (6) from $107.47
Avg. Customer Rating:  5 reviews
Sales Rank: 487108
Media: Hardcover
Number Of Items: 1
Pages: 496
Shipping Weight (lbs): 1.7
Dimensions (in): 9.4 x 6.2 x 1.1
ISBN: 0195115384
Dewey Decimal Number: 550.72
EAN: 9780195115383
ASIN: 0195115384
Publication Date: September 18, 1997
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| Editorial Reviews:
Product Description
This text fulfills a need for an advanced-level work covering both the theory and application of geostatistics. It covers the most important areas of geostatistical methodology, introducing tools for description, quantitative modeling of spatial continuity, spatial prediction, and assessment of local uncertainty and stochastic simulation. It also details the theoretical background underlying most GSLIB programs. The tools are applied to an environmental data set, but the book includes a general presentation of algorithms intended for students and practitioners in such diverse fields as soil science, mining, petroleum, remote sensing, hydrogeology, and the environmental sciences.
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| Customer Reviews:
 A comprehensive treatment March 12, 2007
2 out of 2 found this review helpful
Please be aware that Dr Merk's comment reflects his views of *all* geostatistics that use random fields, variogram models etc. You can read his page to see his view (which I have never been able to figure out) and look at the AI-GEOSTATS archives for plenty of discussion. In Merks' view, the rest of us are either idiots, lemmings, or have been brainwashed; in most practioner's view, the sort of geostatistics taught in this book has proven to be very useful and seems theoretically-sound.
If you decide that this approach can give useful insight into the natural world (i.e. if you agree with 99% of current practicioners), and especially map and predict, than this book is a thorough, detailed treatment. The dataset is available from the author's home page and also comes with the gstat package of R, so the reader can practice all the techniques.
The sections on co-regionalization are especially strong.
Be aware the notation is somewhat non-standard but it works well, especially for complex co-regionalization equations.
 An invalid variant of mathematical statistics December 5, 2002
0 out of 6 found this review helpful
Geostatistics for Natural Resources Evaluation is another textbook that violates the requirement of functional independence and ignores the concept of degrees of freedom. This author is one of many who believes that the true variance of the distance-weighted average can be replaced with the pseudo kriging variance of a SET of degrees-of-freedom and variance-deprived functionally dependent kriged estimates formely known as distance-weighted averages. Degrees of freedom, too, are missing in this textbook, which seems to suggest that this concept is as redundant as the variance of the single distance-weighted average.
THE book in geostatisctics March 1, 2001
5 out of 6 found this review helpful
This book is the one book one should consult in order to study and apply geostatistics. It is very comprehensive, clear and practical. It presents classical and innovative methods in geostatistics, some of them only now appearing in textbooks.
Great for no statisticians June 23, 2000
5 out of 7 found this review helpful
The book is at first out of reach because of the common notation. After three pages it became self explaining and incredibly usefull. I strongly recommend it to subjets new in geostatistics with a no very strong mathematical background.
One of very few well-written math related books August 7, 1998
19 out of 21 found this review helpful
I picked up this book so that I could understand a geostatisical model I was using for petroleum exploration, and it did a beautiful job of laying out the conceptual framework of the math. As a geologist with not so much mathematical background, I was able to pick through the equations and derivations (which I imagine would be useful for those so inclined) to get at the actual substance. This is a surprisingly readable text for a math book, highly recommended.
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