MATLAB® Recipes for Earth Sciences [Hardcover]

Martin H. Trauth (Author), E. Sillmann (Illustrator), R. Gebbers (Contributor), N. Marwan (Contributor)

Book Description

ISBN-10: 3540727485 | ISBN-13: 978-3540727484 | Publication Date: July 20, 2007 | Edition: 2nd

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 methods of data analysis in geosciences using MATLAB such as basic statistics for univariate, bivariate and multivariate datasets, jackknife and bootstrap resampling schemes, processing of digital elevation models, gridding and contouring, geostatistics and kriging, processing and georeferencing of satellite images, digitizing from the screen, linear and nonlinear time-series analysis and the application of linear time-invariant and adaptive filters. The revised and updated Second Edition includes new subchapters on windowed Blackman-Tukey, Lomb-Scargle and Wavelet powerspectral analysis, statistical analysis of point distributions and digital elevation models, and a full new chapter on the statistical analysis of directional data. 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.

Editorial Reviews

Review

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.

From the Back Cover

MATLAB® is used for a wide range of applications in geosciences, such as image processing in remote sensing, the generation and processing of digital elevation models, and the analysis of time series. This book introduces methods of data analysis in geosciences using MATLAB, such as basic statistics for univariate, bivariate and multivariate datasets, jackknife and bootstrap resampling schemes, processing of digital elevation models, gridding and contouring, geostatistics and kriging, processing and georeferencing of satellite images, digitizing from the screen, linear and nonlinear time-series analysis, and the application of linear time-invariant and adaptive filters. The revised and updated Third Edition includes ten new sections and has greatly expanded on most chapters from the previous edition, including a step by step discussion of all methods before demonstrating the methods with MATLAB functions. New sections include: Data Storage and Handling, Data Structures and Classes of Objects, Generating M-Files to Regenerate Graphs, Publishing M-Files, Distribution Fitting, Nonlinear and Weighted Regression, Color-Intensity Transects of Varved Sediments, and Grain Size Analysis from Microscope Images. The text includes 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. --This text refers to an alternate Hardcover edition.

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Product Details

• Hardcover: 288 pages
• Publisher: Springer; 2nd edition (July 20, 2007)
• Language: English
• ISBN-10: 3540727485
• ISBN-13: 978-3540727484
• Product Dimensions: 9.3 x 6.1 x 0.9 inches
• Shipping Weight: 1.4 pounds
• Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #1,362,475 in Books (See Top 100 in Books)

More About the Author

Martin Trauth was born in Landau/Pfalz in 1963 and studied geophysics and geology at the University of Karlsruhe. He obtained a doctoral degree at Kiel University in 1995 and then became a permanent member of the scientific staff and lecturer at the University of Potsdam. Following his Habilitation in 2003, he became Privatdozent at the same university. Since 1990 he has worked on various aspects of historical climate changes in East Africa and South America. His projects aim to understand the role of the tropics in terminating ice ages, the relationship between climate changes and human evolution, and the influence that climate anomalies had on mass movements in the Central Andes. All of these projects include the application of MATLAB- based numerical and statistical methods, such as time-series analysis and signal processing on paleoclimate time series, lake-balance modeling, stochastic modeling of bioturbation, and image processing on laminated sediments. Martin Trauth has been teaching various courses on data analysis in earth sciences for more than ten years, both at the University of Potsdam and at other European universities.

Customer Reviews

Most Helpful Customer Reviews

6 of 6 people found the following review helpful:

4.0 out of 5 stars A good recipe book on a topic that is rarely written about, July 4, 2008

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calvinnme - See all my reviews
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This review is from: MATLAB® Recipes for Earth Sciences (Kindle Edition)

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.