MATLAB and Python Recipes for Earth Sciences
Martin H. Trauth, University of Potsdam, Germany
AI changed everything, also the way we search for literature, create figures, and write summaries. Teaching a course on collecting, processing and presenting geoscientific information and having published two editions of a book on the topic, it was time for a change. And two new books. Continue reading “Collecting, Processing, and Presenting in the Age of AI”
As in previous years, the Python and MATLAS Recipes for Earth Sciences books are once again in the top 100 at Springer Earth Sciences & Environment. Many thanks to all my readers who still buy the books, some of them in print, even though they are sold by Springer in large bundles to libraries!
Young people—as I was back then—do not really appreciate how quickly their valuable data, painstakingly created graphics, and carefully crafted texts can become unreadable. Here are a few thoughts on this and a recommendation. Continue reading “Sustainability of Geoscientific Information”
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 of our geoscience masters program – from processing this year’s masters applications suggests. Continue reading “How to Become a Geoscience Data Analyst”
Detecting, measuring and classifying transitions in climate time series is one of the most important applications in modern time series analysis (Mudelsee, 2000; Trauth et al., 2014, 2025). Three methods are presented here: sigmoid fit, ramp fit and change point detection. Continue reading “Analyzing Climate Transitions with MATLAB”
On April 1, 2022, a satellite was launched as part of the German Environmental Mapping and Analysis Program (EnMAP) to collect hyperspectral data, which can be obtained free of charge. Here is a MATLAB script to import and display the data and display the spectra of single pixels selected from an EnMAP image.
Continue reading “Displaying Single Pixel Spectra from EnMAP Hyperspectral Images with MATLAB”
On April 1, 2022, a satellite was launched as part of the German Environmental Mapping and Analysis Program (EnMAP) to collect hyperspectral data, which can be obtained free of charge. Here is a MATLAB script to import and display the data and display the spectra of single pixels selected from an EnMAP image.
Continue reading “Displaying Flatfield Spectra from EnMAP Hyperspectral Images with MATLAB”
The USGS spectral library is an important database of mineral spectra, which is used as a reference for the spectrometric determination of unknown substances. Here is a simple MATLAB program that can be used to load and display the spectra of several minerals. Continue reading “Importing and Displaying USGS Spectral Library Data with MATLAB”