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Kategorie szczegółowe BISAC

Matlab(r) Recipes for Earth Sciences

ISBN-13: 9783030384432 / Angielski / Miękka / 2021

Martin H. Trauth
Matlab(r) Recipes for Earth Sciences Trauth, Martin H. 9783030384432 Springer International Publishing - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Matlab(r) Recipes for Earth Sciences

ISBN-13: 9783030384432 / Angielski / Miękka / 2021

Martin H. Trauth
cena 201,72 zł
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MATLAB® is used in a wide range of geoscientific applications, e.g. for image processing in remote sensing, for creating and processing digital elevation models, and for analyzing time series. This book introduces readers to MATLAB-based data analysis methods used in the geosciences, including basic statistics for univariate, bivariate and multivariate datasets, time-series analysis, signal processing, the analysis of spatial and directional data, and image analysis. The revised and updated Fifth Edition includes seven new sections, and the majority of the chapters have been rewritten and significantly expanded. New sections include error analysis, the problem of classical linear regression of log-transformed data, aligning stratigraphic sequences, the Normalized Difference Vegetation Index, Aitchison’s log-ratio transformation, graphical representation of spherical data, and statistics of spherical data. The book also includes numerous examples demonstrating how MATLAB can be used on datasets from the earth sciences. The supplementary electronic material (available online through SpringerLink) contains recipes that include all the MATLAB commands featured in the book and the sample data.

Kategorie:
Nauka, Geografia
Kategorie BISAC:
Science > Earth Sciences - Geology
Computers > Computer Simulation
Mathematics > Matematyka stosowana
Wydawca:
Springer International Publishing
Seria wydawnicza:
Springer Textbooks in Earth Sciences, Geography and Environm
Język:
Angielski
ISBN-13:
9783030384432
Rok wydania:
2021
Waga:
0.95 kg
Wymiary:
23.5 x 15.5
Oprawa:
Miękka

Data Analysis in Earth Sciences.- Introduction to MATLAB.- Univariate Statistics.- Bivariate Statistics.- Time-Series Analysis.- Signal Processing.- Spatial Data.- Image Processing.- Multivariate Statistics.- Statistics on Directional Data.

Martin H. Trauth studied geophysics and geology at the University of Karlsruhe. He obtained a doctoral degree from the University of Kiel in 1995 and then became a permanent member of the scientific staff at the University of Potsdam. Following his habilitation in 2003 he became a lecturer, and then in 2011 a titular professor at the University of Potsdam. Since 1990 he has worked on various aspects of past changes in the climates of East Africa and South America. His projects have aimed to understand the role of the tropics in terminating ice ages, the relationship between climatic changes and human evolution, and the influence that climate anomalies had on mass movements in the central Andes. Each of these projects has involved the use of MATLAB to apply numerical and statistical methods (such as time-series analysis and signal processing) to paleoclimate time series, lake-balance modeling, stochastic modeling of bioturbation, age-depth modeling of sedimentary sequences, or the processing of satellite and microscope images. Martin H. Trauth has been teaching a variety of courses on data analysis in earth sciences with MATLAB for more than 25 years, both at the University of Potsdam and at other universities around the world.

MATLAB® is used in a wide range of geoscientific applications, e.g. for image processing in remote sensing, for creating and processing digital elevation models, and for analyzing time series. This book introduces readers to MATLAB-based data analysis methods used in the geosciences, including basic statistics for univariate, bivariate and multivariate datasets, time-series analysis, signal processing, the analysis of spatial and directional data, and image analysis. The revised and updated Fifth Edition includes seven new sections, and the majority of the chapters have been rewritten and significantly expanded. New sections include error analysis, the problem of classical linear regression of log-transformed data, aligning stratigraphic sequences, the Normalized Difference Vegetation Index, Aitchison’s log-ratio transformation, graphical representation of spherical data, and statistics of spherical data. The book also includes numerous examples demonstrating how MATLAB can be used on datasets from the earth sciences. The supplementary electronic material (available online through SpringerLink) contains recipes that include all the MATLAB commands featured in the book and the sample data.



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