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MATLAB® Recipes for Earth Sciences [Hardcover]

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Item description for MATLAB® Recipes for Earth Sciences by Robin Gebbers Martin H. Trauth...

MATLAB is used in a wide range of applications in geosciences, such as image processing in remote sensing, generation and processing of digital elevation models and the analysis of time series. This book introduces basic methods of data analysis in geosciences using MATLAB. The text includes a brief description of each method and numerous examples demonstrating how MATLAB can be used on data sets from earth sciences. All MATLAB recipes can be easily modified in order to analyse the reader's own data sets. The book comes with a CD containing exemplary data sets and a digital version of the MATLAB recipes.

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Item Specifications...

Pages   238
Est. Packaging Dimensions:   Length: 9.29" Width: 6.22" Height: 0.79"
Weight:   1.32 lbs.
Binding  Hardcover
Release Date   Mar 14, 2006
Publisher   Springer
ISBN  3540279830  
ISBN13  9783540279839  

Availability  0 units.

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Product Categories

1Books > Special Features > Formats
2Books > Special Features > New & Used Textbooks > Sciences > Earth Sciences
3Books > Subjects > Professional & Technical > Professional Science > Earth Sciences > General
4Books > Subjects > Professional & Technical > Professional Science > Earth Sciences > Geology
5Books > Subjects > Science > Earth Sciences > General
6Books > Subjects > Science > General

Reviews - What do customers think about MATLAB® Recipes for Earth Sciences?

A good recipe book on a topic that is rarely written about  Jul 4, 2008
At first glance the book seems a bit skinny for the pricetag, but the book contains well-written recipes for specialized tasks often needed in remote sensing. I found the book easy to comprehend, well-illustrated, and the code well commented. Like the other reviewer, I found the recipes easily translated to other languages. The following is the table of contents, shown here because it is vital for knowing whether or not this book is for you and because the table of contents can be hard to find:

1. Data Analysis in Earth Sciences
2. Introduction to Matlab
3. Univariate Statistics
4. Bivariate Statistics
5. Time-Series Analysis
6. Signal Processing
7. Spatial Data
8. Image Processing
9. Multivariate Statistics
10. Statistics on Directional Data

This book is a little light on image processing, if that is your interest. There's already a good book on Matlab and imaging - Digital Image Processing Using MATLAB(R). None of the chapters are so much about the science - signal processing, statistics, etc. - as they are about how to accomplish tasks in Matlab. You'll need other books if you are unfamiliar with the terms. You'll also need a good basic book on introductory Matlab, since one chapter is not enough to get you going. I suggest either Getting Started with MATLAB 7: A Quick Introduction for Scientists and Engineers (The Oxford Series in Electrical and Computer Engineering) or Mastering MATLAB 7.

If you already know the science and you know the basics of Matlab, and you just wonder "How do you do this in Matlab?" this book is for you.
Recipes for Earth Science  Feb 16, 2008
This is a well written, perhaps slightly overpriced book, providing an overview and starting point for a wide range of applications in geosciences, such as image processing in remote sensing, generation and processing of digital elevation models and the analysis of time series - as stated. Also, as stated, the book introduces methods of data analysis in geosciences using MATLAB. I purchased the book for the "applications in geosciences" part and not the "MATLAB" part. I have nothing, in particular, against using MATLAB, but I choose to use Python. Python is free, and I (and many, many others) believe it to provide more manageable and powerful numerical analysis capabilities as well as better overall peripheral integration (integrating with other programming languages, applications, OS systems, or other platform specifics). The nice thing about the book is that the MATLAB code snippets and brief implementation explanations, can be easily translated into python implementation. If you are tied to MATLAB, I don't think you will be disappointed. If you have some familiarity with python then you will also be able to glean allot from the content. Another reason that I enjoy this book, is that while it relies on quite a bit of advanced math and its application, it uses the math as an 'engineering type' book should - as a tool to use to solve a problem. The mathematical element flows nicely with the subject matter and I suspect that even an individual without a mathematics background could gain an appreciation for the math based on the context and would not necessarily need to know or learn every underlying aspect of theory that generated the mathematics used. This is refreshing to see in an advanced book - here is what you might be up against, here is what you need to get the job done.

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