The course (in Englisch and German language) introduces methods of data analysis in earth and environmental sciences using MATLAB, one of the leading software packages for the solution of mathematical problems. 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.
Data analysis in earth and environmental sciences, types of data, overview of methods, introduction to the MATLAB programming environment. MATLAB 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, in particular 3D objects, series of images and movies, to be included in animated eBooks and webpages with MATLAB results.
The course is being taught as lecture with demonstrations and exercises on selected examples from the earth and environmental sciences. The course location is a seminar room at the Department of Earth and Environmental Science at the University of Potsdam. The participants are expected to come with personal laptops running Windows, Linux, or Mac OS X. A temporary license of MATLAB will be provided by the organizers.
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 and U Potsdam.
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)