Online Shortcourse on MATLAB/Python Recipes for Earth Sciences


The online course (in Englisch and German language) introduces methods of data analysis in earth and environmental sciences using MATLAB and Python. The content of the course includes basic statistics for univariate, bivariate and multivariate datasets, time-series analysis and signal processing, processing and displaying digital elevation models, gridding and contouring, and image processing and analysis.

Course Program

Data analysis in earth and environmental sciences, types of data, overview of methods, introduction to the MATLAB and Python programming environment. MATLAB and Python syntax, import and export of data, types of data, scripts and functions, basic visualization techniques. Univariate statistics, theoretical distributions, hypothesis testing. Bivariate statistics, regression, bootstrap and jackknife, reduced major axis regression, nonlinear weighted regression. Time-series analysis, Blackman-Tukey spectral analysis, periodogram, evolutionary spectrum, Lomb-Scargle method, Wavelets. Signal processing, convolution and filtering, filter design, adaptive filters. Analysis of spatial data, digital terrain models, spatial interpolation, visualization of spatial data. Multivariate statistics, principal component analysis, cluster analysis. Image processing and analysis, processing and georeferencing satellite images, image analysis of microscope images, quantification of objects in images. Exporting graphics from MATLAB and Python, in particular 3D objects, series of images and movies, to be included in animated eBooks and webpages with MATLAB and Python results.


The course was taught at the U Aberystwyth, U Addis Ababa, U Bremen, U Bratislava, U Ghent, UA Barcelona, BGR Hannover, U Kiel, UC London, LMU München, BGI Bayreuth, U Nairobi, U Köln, U Stockholm, U Amsterdam, NHM Vienna, GNS Science Wellington, Brown U Providence, U Arizona Tucson, U Fribourg and U Potsdam.

The books

Trauth, M.H., Sillmann, E. (2018) Collecting, Processing and Presenting Geoscientific Information, MATLAB® and Design Recipes for Earth Sciences – Second Edition. Springer International Publishing, 274 p., Supplementary Electronic Material, Hardcover, ISBN: 978-3-662-56202-4. (MDRES)

Trauth, M.H. (2021) Signal and Noise in Geosciences, MATLAB Recipes for Data Acquisition in Earth Sciences. Springer International Publishing, 343 p., Supplementary Electronic Material, Hardcover, ISBN: 978-3-030-74912-5 (MRDAES)

Trauth, M.H. (2021) MATLAB Recipes for Earth Sciences – Fifth Edition. Springer International Publishing, 517 p., Supplementary Electronic Material, Hardcover, ISBN: 978-3-030-38440-1. (MRES)

Trauth, M.H. (2022) MATLAB®-Rezepte für die Geowissenschaften, 1. deutschsprachige Auflage, basierend auf der 5. englischsprachigen Auflage. Springer Spektrum, ISBN 978-3-662-64356-3 (MRG)

Trauth, M.H. (2022) Python Recipes for Earth Sciences – First Edition. Springer International Publishing, ~500 p., Supplementary Electronic Material, Hardcover, ISBN 978-3-031-07718-0. (PRES)