MATLAB Recipes for Earth Sciences by Martin H. Trauth
Various books on data analysis in earth sciences have been published during the last ten years, such as Statistics and Data Analysis in Geology by JC Davis,
Introduction to Geological Data Analysis by ARH Swan and M Sandilands, Data Analysis in the Earth Sciences Using MATLAB® by GV Middleton or Statistics of Earth Science Data by G Borradaile. Moreover, a number of software packages have been designed for earth scientists such as the ESRI product suite ArcGIS or the freeware package GRASS for generating geographic information systems, ERDAS IMAGINE or RSINC ENVI for remote sensing and GOCAD and SURFER for 3D modeling of geologic features. In addition, more general software packages as IDL by RSINC and MATLAB® by The MathWorks Inc. or the freeware software OCTAVE provide powerful tools for the analysis and visualization of data in earth sciences.
Most books on geological data analysis contain excellent theoretical introductions, but no computer solutions to typical problems in earth sciences, such as the book by JC Davis. The book by ARH Swan and M Sandilands contains a number of examples, but without the use of computers. G Middleton·s book fi rstly introduces MATLAB as a tool for earth scientists, but the content of the book mainly refl ects the personal interests of the author, rather then providing a complete introduction to geological data analysis. On the software side, earth scientists often encounter the problem that a certain piece of software is designed to solve a particular geologic problem, such as the design of a geoinformation system or the 3D visualization of a fault scarp. Therefore, earth scientists have to buy a large volume of software products, and even more important, they have to get used to itbefore being in the position to successfully use it.
This book on MATLAB Recipes for Earth Sciences is designed to help undergraduate and PhD students, postdocs and professionals to learn methods of data analysis in earth sciences and to get familiar with MATLAB, the leading software for numerical computations. The title of the book is
an appreciation of the book Numerical Recipes by WH Press and others that is still very popular after initially being published in 1986. Similar to the book by Press and others,
1. Chapter 1 – This chapter introduces some fundamental concepts of sam-
ples and populations, it links the various types of data and questions to
be answered from these data to the methods described in the following
chapters.
2. 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 following chapters.
3. Chapter 3 and 4 – Fundamentals in univariate and bivariate statistics.
These chapters contain very basic things how statistics works, but also
introduce some more advanced topics such as the use of surrogates. The
reader already familiar with basic statistics might skip these two chap-
ters.
4. Chapter 5 and 6 – Readers who wish to work with time series are recom-
mended to read both chapters. Time-series analysis and signal processing
are tightly linked. A solid knowledge of statistics is required to success-
fully work with these methods. However, the two chapters are more or
less independent from the previous chapters.
5. Chapter 7 and 8 – The second pair of chapters. From my experience,
reading both chapters makes a lot of sense. Processing gridded spatial
data and analyzing images has a number of similarities. Moreover, aerial
photographs and satellite images are often projected upon digital eleva-
tion models.
6. Chapter 9 – Data sets in earth sciences are tremendously increasing in the
number of variables and data points. Multivariate methods are applied to
a great variety of types of large data sets, including even satellite images.
The reader particularly interested in multivariate methods is advised to
read Chapters 3 and 4 before proceeding to this chapter.
I hope that the various readers will now fi nd their way through the book.
Experienced MATLAB users familiar with basic statistics are invited to pro-
ceed to Chapters 5 and 6 (the time series), Chapters 7 and 8 (spatial data and
images) or Chapter 9 (multivariate analysis) immediately, which contain
both an introduction to the subjects as well as very advanced and special
procedures for analyzing data in earth sciences. It is recommended to the
beginners, however, to read Chapters 1 to 4 carefully before getting into the
advanced methods.
I thank the NASA/GSFC/METI/ERSDAC/JAROS and U.S./Japan ASTER
Science Team and the director Mike Abrams for allowing me to include the
ASTER images in the book. The book has benefi t from the comments of a
large number of colleagues and students. I gratefully acknowledge my col-
leagues who commented earlier versions of the manuscript, namely Robin
Gebbers, Norbert Marwan, Ira Ojala, Lydia Olaka, Jim Renwick, Jochen
Rössler, Rolf Romer, and Annette Witt. Thanks also to the students Mathis
Hein, Stefanie von Lonski and Matthias Gerber, who helped me to improve
the book. I very much appreciate the expertise and patience of Elisabeth
Sillmann who created the graphics and the complete page design of the
book. I also acknowledge Courtney Esposito leading the author program at
The MathWorks, Claudia Olrogge and Annegret Schumann at Mathworks
Deutschland, Wolfgang Engel at Springer, Andreas Bohlen and Brunhilde
Schulz at UP Transfer GmbH. I would like to thank Thomas Schulmeister
who helped me to get a campus license for MATLAB at Potsdam University.
The book is dedicated to Peter Koch, the late system administrator of the
Department of Geosciences who died during the fi nal writing stages of the
manuscript and who helped me in all kinds of computer problems during the
last few years.
Introduction to Geological Data Analysis by ARH Swan and M Sandilands, Data Analysis in the Earth Sciences Using MATLAB® by GV Middleton or Statistics of Earth Science Data by G Borradaile. Moreover, a number of software packages have been designed for earth scientists such as the ESRI product suite ArcGIS or the freeware package GRASS for generating geographic information systems, ERDAS IMAGINE or RSINC ENVI for remote sensing and GOCAD and SURFER for 3D modeling of geologic features. In addition, more general software packages as IDL by RSINC and MATLAB® by The MathWorks Inc. or the freeware software OCTAVE provide powerful tools for the analysis and visualization of data in earth sciences.
Most books on geological data analysis contain excellent theoretical introductions, but no computer solutions to typical problems in earth sciences, such as the book by JC Davis. The book by ARH Swan and M Sandilands contains a number of examples, but without the use of computers. G Middleton·s book fi rstly introduces MATLAB as a tool for earth scientists, but the content of the book mainly refl ects the personal interests of the author, rather then providing a complete introduction to geological data analysis. On the software side, earth scientists often encounter the problem that a certain piece of software is designed to solve a particular geologic problem, such as the design of a geoinformation system or the 3D visualization of a fault scarp. Therefore, earth scientists have to buy a large volume of software products, and even more important, they have to get used to itbefore being in the position to successfully use it.
This book on MATLAB Recipes for Earth Sciences is designed to help undergraduate and PhD students, postdocs and professionals to learn methods of data analysis in earth sciences and to get familiar with MATLAB, the leading software for numerical computations. The title of the book is
an appreciation of the book Numerical Recipes by WH Press and others that is still very popular after initially being published in 1986. Similar to the book by Press and others,
1. Chapter 1 – This chapter introduces some fundamental concepts of sam-
ples and populations, it links the various types of data and questions to
be answered from these data to the methods described in the following
chapters.
2. 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 following chapters.
3. Chapter 3 and 4 – Fundamentals in univariate and bivariate statistics.
These chapters contain very basic things how statistics works, but also
introduce some more advanced topics such as the use of surrogates. The
reader already familiar with basic statistics might skip these two chap-
ters.
4. Chapter 5 and 6 – Readers who wish to work with time series are recom-
mended to read both chapters. Time-series analysis and signal processing
are tightly linked. A solid knowledge of statistics is required to success-
fully work with these methods. However, the two chapters are more or
less independent from the previous chapters.
5. Chapter 7 and 8 – The second pair of chapters. From my experience,
reading both chapters makes a lot of sense. Processing gridded spatial
data and analyzing images has a number of similarities. Moreover, aerial
photographs and satellite images are often projected upon digital eleva-
tion models.
6. Chapter 9 – Data sets in earth sciences are tremendously increasing in the
number of variables and data points. Multivariate methods are applied to
a great variety of types of large data sets, including even satellite images.
The reader particularly interested in multivariate methods is advised to
read Chapters 3 and 4 before proceeding to this chapter.
I hope that the various readers will now fi nd their way through the book.
Experienced MATLAB users familiar with basic statistics are invited to pro-
ceed to Chapters 5 and 6 (the time series), Chapters 7 and 8 (spatial data and
images) or Chapter 9 (multivariate analysis) immediately, which contain
both an introduction to the subjects as well as very advanced and special
procedures for analyzing data in earth sciences. It is recommended to the
beginners, however, to read Chapters 1 to 4 carefully before getting into the
advanced methods.
I thank the NASA/GSFC/METI/ERSDAC/JAROS and U.S./Japan ASTER
Science Team and the director Mike Abrams for allowing me to include the
ASTER images in the book. The book has benefi t from the comments of a
large number of colleagues and students. I gratefully acknowledge my col-
leagues who commented earlier versions of the manuscript, namely Robin
Gebbers, Norbert Marwan, Ira Ojala, Lydia Olaka, Jim Renwick, Jochen
Rössler, Rolf Romer, and Annette Witt. Thanks also to the students Mathis
Hein, Stefanie von Lonski and Matthias Gerber, who helped me to improve
the book. I very much appreciate the expertise and patience of Elisabeth
Sillmann who created the graphics and the complete page design of the
book. I also acknowledge Courtney Esposito leading the author program at
The MathWorks, Claudia Olrogge and Annegret Schumann at Mathworks
Deutschland, Wolfgang Engel at Springer, Andreas Bohlen and Brunhilde
Schulz at UP Transfer GmbH. I would like to thank Thomas Schulmeister
who helped me to get a campus license for MATLAB at Potsdam University.
The book is dedicated to Peter Koch, the late system administrator of the
Department of Geosciences who died during the fi nal writing stages of the
manuscript and who helped me in all kinds of computer problems during the
last few years.
Buy: MATLAB Recipes for Earth Sciences Paperback – 12 Oct 2016 by Martin H. Trauth (Author)
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