Customer Reviews

Basic Linear Geostatistics

5 star:		(3)
4 star:		(1)
3 star:		(0)
2 star:		(0)
1 star:		(0)

 

 

This book treats some stuffs in geostatistics including basic stochastic theory, variogram, and various kriging techniques. Though this is an introductory textbook of geostatistics, it's theoretical approach and explanation are clear, creative, and easy to understanding for students who are new to this area. I would like to recommend this book for all of students who have an interest in geostatistics and for experts too.

It is a very good text book for bachelor degree level, but, the book could be better if the pictures were designed again with powered tools. There is very good examples, but a primitive picture make it look not so good.

This book treats some stuffs in geostatistics including basic stochastic theory, variogram, and various kriging techniques. Though this is an introductory textbook of geostatistics, it's theoretical approach and explanation are clear, creative, and easy to understanding for students who are new to this area. I would like to recommend this book for all of students who have an interest in geostatistics and for experts too.

This text explains in plain english, in a quite readable way, the basics of basic geostatistics. By basics I mean some background statistical theory (stationarity, inherent hypothesis), covariances, variograms, simple kriging and ordinary kriging. The book does not cover universal kriging, disjunctive kriging, indicator kriging, etc. The book is clearly focused on engineers for the mining industry as all of the terminology comes from mining as do all of the examples. Not being in the mining industry I found following some of the examples difficult due to not understanding mining terminology.

While the preface indicates this text is intended for a postgraduate course, I find this hard to believe. The level of the mathematics and the text seems more appropriate for an undergraduate course. Where the text excels is in accompanying each new element of the theory with concrete examples on real data. The reader can work the examples and see what the theory means. A lot of the geostatistics journal literature presupposes that you've read something like this text and have digested it.

The text contain typos in some of its equations - generally easy to spot, but annoying none the less. It seems clear that this text didn't get much in the way of editorial guidance or review. And in some instances, it appears a technical review should have been done. In one example from section 2.4, Armstrong ascribes to stationarity "This makes statistical inference possible on a single realization" what should be ascribed to ergodicity.

For more theoretical and more comprehensive coverage, the texts by Cressie (Statistics for Spatial Data) or by Chiles and Delfiner (Geostatistics: Modeling Spatial Uncertainty) are quite good. I give this four stars because it's a very readable text for learning the basics and clearing up stuff left unstated or assumed known when you first read something like Cressie's text (I read that first) and it's examples are extremely helpful in understanding - too few textbooks use such examples when attempting to teach basic theory.