MATLAB® Recipes for Earth Sciences: Recipes for Data Analysis

Martin H. Trauth

ISBN 10: 3540279830 / ISBN 13: 9783540279839

Published by Springer, 2006

About this Item

Aufl. 2006, Bibliotheksexemplar, CD fehlt * Einband: Ecken angestoßen * Seiten: wie ungelesen.

Seller Inventory # RN-LN7S-VWM3

Bibliographic Details

• Title: MATLAB® Recipes for Earth Sciences: Recipes for Data Analysis
• Publisher: Springer
• Publication Date: 2006
• Language: English
• ISBN 10: 3540279830
• ISBN 13: 9783540279839
• Binding: Gebundene Ausgabe
• Illustrator: Sillmann, E.
• Condition: Ausreichend

About this title

Synopsis

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 on how MATLAB can be used on data sets from earth sciences. All MATLAB recipes can easily be modified in order to analyse the reader's own data sets. The book comes with a CD containing example data sets and a digital version of the MATLAB recipes.

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 anadvanced book - here is what you might be up against, here is what you need to get the job done.