Author: Martin H. Trauth

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”

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”

If your MATLAB script is too slow you may wish to find out in which part of the script the time is wasted. There are many ways to find the time consuming part of the script, for example the Profiler function Run and Time, but the simplest way is tic and toc to be included in a MATLAB script. Continue reading “Speeding Up Your MATLAB Code and Using the Stopwatch Timer”

Creating Graphical User Interfaces (GUIs) with MATLAB is very easy and can be done either by coding the GUI entirely in the MATLAB Editor, by using the GUI Design Environment (GUIDE) or the new MATLAB App Designer. Here is an example for creating a GUI with GUIDE within ten minutes. Continue reading “Creating Graphical User Interfaces with MATLAB in Ten Minutes”

On September 29, 2017, the University of Potsdam will once again open its lecture halls for children to inspire them with the world of science. On this day, children can listen to interesting lectures, discuss with the scientists, and can experience exciting experiments. On Friday 29 September 2017 I will give a public lecture on tectonics, climate and human evolution for 8–10 year old children. Please visit the webpage of the children’s university to learn more about the event and how to register.

During a workshop on time series analysis on paleoclimatic data, I was asked how data gaps affect the results of spectral analyzes. The good news is, the expected climatic cycles such as Milankovitch cycles do not shift when the time series has gaps. However, it is important that the data is properly pre-treated before being examined with a method of spectral analysis. Continue reading “Data Voids and Spectral Analysis: Don’t Be Afraid Of Gaps!”

The VolkswagenFoundation funds a series of two summer schools entitled “Earth Surface Dynamics – Understanding Processes at the Earth’s Vulnerable Skin”. Here are some details about the content of the modules of the summer school. Continue reading “Summer School 2018 on Earth Surface Dynamics, Part 4”

Using the MAPIR Survey2 cameras described in an earlier post I took photos of the car park next to our departmental building. The relatively inexpensive multispectral array consists of four cameras, ~340 € each, recording NDVI Red+NIR (650 and 850 nm), Blue (450 nm), Green (550 nm) and Visible Light RGB (~370–650 nm). We use the four cameras to build a multispectral array, possibly mounted on drones, to determine various types of minerals, vegetation, and man-made materials on the ground.

Continue reading “Using a Multispectral Array with MATLAB, Part 2”