Today the University of Potsdam published an article by Matthias Zimmermann about the MATLAB/LEGO MINDSTORMS practical, sponsored by MathWorks Inc. The practical, part of the master’s courses “Geosciences” and “Remote Sensing, geoInformation and Visualization“, as well as of the Summer School on Earth Surface Dynamics, aims to improve student’s skills to build efficient teams to solve typical problems in earth sciences in acquiring, processing and analyzing typical multispectral (visible, infrared, thermal), geophysical (seismic, magnetic) and geometric (2D, 3D) data. Photo: Karla Fritze.
At the moment we are very busy with the calculation of recurrence plots in the working group. One of my doctoral students complained that his MATLAB installation often crashes due to Java problems after the calculation has been running for a while. Of course you can try to solve the Java problems. On the other hand, you can also completely avoid the MATLAB user interface. Here is how.
Continue reading “Launching MATLAB Without the Java Desktop”
The 2nd edition of the book MATLAB® and Design Recipes for Earth Sciences (MDRES), together with designer Elisabeth Sillmann, was submitted to Springer International Publishing AG today. Different from the first edition shown on the right hand side, the book’s new title is Collecting, Processing and Presenting Geoscientific Information with the subtitle MATLAB® and Design Recipes for Earth Sciences. The book has been thoroughly reworked and includes a 12th chapter on Creating Multimedia Publications.
The book “MATLAB Recipes for Earth Sciences” (Springer, 2015) is ranked 7th (August 2017) in the Top 100 out of more than 4,600 books in Earth Sciences, Geography & Environment of Springer. Thanks to all readers for buying the book!
The Principal Component Analysis (PCA) is equivalent to fitting an n-dimensional ellipsoid to the data, where the eigenvectors of the covariance matrix of the data set are the axes of the ellipsoid. The eigenvalues represent the distribution of the variance among each of the eigenvectors. To understand the method, it is helpful to know something about matrix algebra, eigenvectors, and eigenvalues. Here is a n=2 dimensional example to perform a PCA without the use of the MATLAB function pca, but with the function of eig for the calculation of eigenvectors and eigenvalues. Continue reading “Principal Component Analysis in 6 Steps”
Working with quantitative data, which requires sophisticated mathematical and computer-assisted evaluation methods, came very late in the geological sciences, compared to other scientific disciplines. Unfortunately, in many geology courses worldwide university-level mathematics and computational geosciences is not included, as my experience – as the current chair of the examination committee – from processing this year’s masters applications suggests. Continue reading “How to Become a Geoscience Data Analyst”
Colormaps are a graphical representation of data values as colors. MATLAB has a number of builtin colormaps. If you are tired of these there are several options to create and use alternative colormaps. Continue reading “Using Colormaps with MATLAB”