2010_Book_MATLABRecipesForEarthSciences.pdf对于地球科学专

文件名称: 2010_Book_MATLABRecipesForEarthSciences.pdf

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详细说明：对于地球科学专业的学者来说，此教程有很好的指导作用，能够帮助快速上手，快速了解matlab在地学当中的用途和操作方法。Martin h. trauth MATLAB③ Recipes for earth sciences Third edition With Contributions by Robin gebbers and norbert marwan and illustrations by Elisabeth Sillmann ②s ringer Privatdozent dr rer. nat. habil. martin h. trauth University of potsdam Department of Earth and Environmental Sciences Karl-Liebknecht-Str 24 14476 Potsdam ermany trauth geo. uni-potsdam de ISBN978-3-642-12761-8 e-ISBN978-3-642-12762-5 DOI10.1007/978-3-642-12762-5 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2010930277 C Springer-Verlag Berlin Heidelberg 2006, 2007, 2010 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use TYpesettingandbookdesignbyElisabethSillmann,www.blaetterwalddesign.deLandauGermany Cover design: deblik, Berlin Printed on acid-free paper SpringerispartofSpringerScience+businessMedia(www.springer.com) Preface The book MaTlaB Recipes for Earth Sciences is designed to help under- graduates, and PhD students, post-doctoral researchers, and professionals find quick solutions for common problems in data analysis in earth sciences It provides a minimum amount of theoretical background, and demon- strates the application of all described methods through the use of exam- ples. The MATLAB software is used since it not only provides numerous ready-to-use algorithms for most methods of data analysis but also allows the existing routines to be modified and expanded, or new software to be developed. The book contains MATLAB scripts, or M-files, to solve typical problems in earth sciences, such as simple statistics, time-series analysis geostatistics, and image processing, and also demonstrates the application of selected advanced techniques of data analysis such as nonlinear time series analysis, adaptive filtering, bootstrapping, and terrain analysis. It comes with a compact disk that contains all matlab recipes and example data files as well as presentation files for instructors. The MaTLaB codes can be easily modified for application to the reader's data and projects This revised and updated Third Edition includes new sections on soft ware-related issues(Sections 2.4, 2.5, 2. 8 and 2.9). Chapter 2 was difficult to update since MatlaB has expanded so much over the years, and i have deliberately tried to restrict this chapter to demonstrating of those tools ac- tually used in the book. A second difficulty arose from the current move by The mathWorks inc to use and incorporate objects and classes in some areas of their Matlab routines, although there does not seem to be any in tention of abandoning the existing procedural code. Again, I have restricted the introduction and use of objects and classes to the absolute minimum even at the expense of omitting one of the new features of maTlaB. Some functions, however, such as those for distribution fitting use this new con- cept of object-oriented programming, and i hope that the reader will forgive me for not explaining all the details of the matlab code when using it The other new sections are on distribution fitting( Section 3.9), and on non- linear and weighted regression(Section 4.10), as these techniques are widely used in, for instance, isotope geochemistry and geochronology. Sections 8.7 PREFACE to 8.9 introduce some advanced methods in image analysis such the ex traction of color-intensity transects from laminated sediments, automatic grain size analysis, and the quantification of charcoal in microscope images These techniques are frequently used in my research projects and are always in demand during the short courses that i teach In order to derive the maximum benefit from this book the reader will need to have access to the matlab software and be able to execute the recipes while reading the book. The MatlaB recipes display various graphs on the screen that are not shown in the printed book. The tutorial- style book does, however, contain numerous figures making it possible to go through the text without actually running MATlAB on a computer. I have developed the recipes using MaTLAB 7 Release r2010a, but most of them will also work with earlier software releases. While undergraduates participating in a course on data analysis might go through the entire book, the more experienced reader may use only one particular method to solve a specific problem. The concept of the book and the contents of its chapters are therefore outlined below in order to make it easier to use for readers with a variety of different requirements Chapter 1-This chapter introduces some fundamental concepts of sam ples and populations. It also links the various types of data, and questions to be answered from the data, to the methods described in the succeeding p Chapter 2-A tutorial-style introduction to MatlaB designed for earth scientists. Readers already familiar with the software are advised to pro ceed directly to the succeeding chapters. The Third Edition now includes new sections on data structures and classes of objects, on generating M-files to regenerate graphs and on publishing m-files Chapters 3 and 4-Fundamentals in univariate and bivariate statistics These two chapters contain basic concepts in statistics, and also introduc es advanced topics such as resampling schemes and cross validation. The reader already familiar with basic statistics might skip these two chapters The Third Edition now includes new sections on fitting normal distribu tions to observations and on nonlinear and weighted regression analysis Chapters 5 and 6- Readers who wish to work with time series are rec- ommended to read both of these chapters. Time-series analysis and signa processing are closely linked. a good knowledge of statistics is required PREFACE VIl to work successfully with these methods. These two chapters are inde- pendent of the preceding chapters Chapters 7 and 8-I recommend reading through both of these chapters since the processing methods used for spatial data and for images have much in common. Moreover, spatial data and images are often combined in earth sciences, for instance when projecting satellite images onto digi tal elevation models. The third edition now includes new sections on color-intensity transects of laminated sediments, automated grain size analysis from photos and quantifying charcoal in microscope images Chapter 9- Data sets in earth sciences often have many variables and many data points. Multivariate methods are applied to a great variety of large data sets, including satellite imagery. any reader particularly inter- ested in multivariate methods is advised to read Chapters 3 and 4 before proceeding to this chapter Chapter 10- Methods to analyze circular and spherical data are wide- ly used in earth sciences. Structural geologists measure and analyze the orientation of slickensides (or striae) on a fault plane. The statisti cal analysis of circular data is also used in paleomagnetic applications Microstructural investigations include the analysis of the grain shapes and quartz c-axis orientations in thin sections While the book matlab Recipes for earth Sciences is about data analy sis it does not attempt to cover modeling. For this subject, I recommend the excellent book Environmental Modeling Using MatlaB by Ekkehard Holzbecher (Springer 2007), which first introduces basic concepts of modeling and then provides a great overview of modeling examples us ing Matlab. holzbecher's book uses a very similar concept to Matlab Recipes for earth Sciences as it gives a brief introduction to the theory, and then explains matlab examples. Neither book provides a complete introduction to all available techniques, but they both provide a quick overview of basic concepts for data analysis and modeling in earth sci- ences. One of the few critical reviewers of the first edition of matlab Recipes for earth Sciences raised the question of why I had not included a chapter on finite-element and finite-difference modeling, and on solv- ing differential equations in his opinion a major omission in the book However, this is far beyond of the scope of the book and my own expertise Students and colleagues interested in this topic are directed to the book PREFACE MATLAB Guide to Finite Elements: An Interactive Approach by Peter I Kattan( Springer 2007). While my book may be considered by some to be a little light on image processing, I have included in Chapter 8 three new sec tions on the analysis of sediment images. I would also strongly recommend to anyone interested in this topic the very successful book Digital Image Processing Using MatlaB by Gonzales, Woods and Eddins( Gatesmark Publishing 2009), for which a 2nd edition has just been published I have taken all other critiques quite seriously and invite all readers to also comment on the Third Edition: the book is constantly changing and evolving. As the Third Edition appears on the bookshelves I will create a new folder on the hard disk of my computer named Fourth edition, where new ideas will be collected. The book has benefited from the comments of many people, in particular my contributing authors Robin Gebbers and Norbert Marwan, my colleagues Ira Ojala, Lydia Olaka, Jim Renwick Jochen Rossler, Rolf Romer, Annette Witt, and the students matthias Gerber. Mathis hain, Martin Homann Stefanie von Lonski, Oliver Rach Marius Walter and Max Zitzmann. I very much appreciate the expertise and patience of Elisabeth Sillmann at blaetterwald Design who created the graphics and the complete page designs of the book i am much obliged to Ed Manning for professional proofreading of the text. I also acknowledge Naomi Fernandez from the book program and Kate Fiore from Academic Support at The Math Works Inc, Claudia Olrogge and Annegret Schumann at The math works gmbh deutschland. christian witschel. Chris bendall and their team at Springer, and andreas bohlen, Brunhilde schulz and their team at UP Transfer gmbH. I also thank the NASA/GSFC/METI/ERSDAC/ JAROS and the u.S. / Japan ASTER Science Team and the director Mike abrams for allowing me to include the aster images in this book Potsdam, April 2010 Martin trauth Contents 1 Data Analysis in Earth Sciences 1.1 Introduction 1.2 Data Collection 1.3 Types of Data 1.4 Methods of data analysis 2 Introduction to matlab 11 2.1 MATLAB in Earth Sciences 2.2 Getting Started 2.3 The Syntax 14 2.4 Data Storage and Handling 18 2.5 Data Structures and Classes of objects 21 2.6 Scripts and Functions 26 2.7 Basic Visualization tools 29 2.8 Generating M-Files to Regenerate Graphs 32 2.9 Publishing M-Files 35 3 Univariate statistics 3.1 Introduction 3.2 Empirical Distributions 37 3.3 Example of Empirical Distributions 44 3.4 Theoretical distributions 51 3.5 Example of Theoretical Distributions 59 3. 6 The t-Test 61 3.7 The F-Test 3.8 Thex-Te est 70 3. 9 Distribution Fitting 73 CONTENTS 4 Bivariate statistics 79 4.1 Introduction 4.2 Pearson's Correlation Coefficient 80 4.3 Classical Linear Regression Analysis and Prediction 88 4. 4 Analyzing the Residuals 4.5 Bootstrap Estimates of the Regression Coefficients 4 4.6 Jackknife estimates of the regression Coefficients 4.7 Cross validation 4.8 Reduced Major Axis Regression 99 4.9 Curvilinear Regression 100 4.10 Nonlinear and Weighted regression 103 5 Time-Series Analysis 107 5.1 Introduction 107 5.2 Generating Signals 108 5.3 Auto-Spectral and Cross-Spectral Analysis 5.4 Examples of Auto-Spectral and Cross-Spectral Analysis 117 5.5 Interpolating and Analyzing Unevenly-Spaced Data 126 5.6 Evolutionary Power Spectrum 131 5.7 Lomb-Scargle power spectrum 135 5.8 Wavelet Power Spectrum 139 5.9 Nonlinear Time-Series Analysis(by N. Marwan 146 Signal Processing 161 6.1 Introduction 161 2 Generating signals 162 6.3 Linear Time-Invariant Systems 164 6.4 Convolution and Filtering 166 5 Comparing Functions for Filtering Data Series 169 6.6 Recursive and nonrecursive filters 172 6.7 Impulse response 173 8 Frequency Response 176 6.9 Filter Design 182 6.10 Adaptive Filtering 185 7 Spatial Data 193 7.1 Types of Spatial Data 193 7.2 The gshhs shoreline data set 194

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