Overview
- Introduces methods of data analysis in geosciences using Python
- Contains a complete collection of computer codes and sample data, as well as an accompanying blog
- Written by an expert for geoscientific modeling programs
Part of the book series: Springer Textbooks in Earth Sciences, Geography and Environment (STEGE)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
Python is used in a wide range of geoscientific applications, such as in processing images for remote sensing, in generating and processing digital elevation models, and in analyzing time series. This book introduces methods of data analysis in the geosciences using Python that include basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, and signal processing; the analysis of spatial and directional data; and image analysis. The text includes numerous examples that demonstrate how Python can be used on data sets from the earth sciences. Codes are available online through GitHub.
Similar content being viewed by others
Keywords
Table of contents (10 chapters)
Authors and Affiliations
About the author
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.
Accessibility Information
Accessibility information for this book is coming soon. We're working to make it available as quickly as possible. Thank you for your patience.
Bibliographic Information
Book Title: Python Recipes for Earth Sciences
Authors: Martin H. Trauth
Series Title: Springer Textbooks in Earth Sciences, Geography and Environment
DOI: https://doi.org/10.1007/978-3-031-56906-7
Publisher: Springer Cham
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Hardcover ISBN: 978-3-031-56905-0Published: 08 October 2024
Softcover ISBN: 978-3-031-56908-1Due: 22 October 2025
eBook ISBN: 978-3-031-56906-7Published: 07 October 2024
Series ISSN: 2510-1307
Series E-ISSN: 2510-1315
Edition Number: 2
Number of Pages: XI, 491
Number of Illustrations: 21 b/w illustrations, 127 illustrations in colour
Topics: Geophysics/Geodesy, Computer Applications, Geography, general