Quantifying Charcoal in Microscope Images Using MATLAB, Part 2

Quantifying the composition of substances in geosciences, such as the mineral composition of a rock in thin sections, or the amount of charcoal in sieved sediment samples, is facilitated by the use of image processing methods. Thresholding provides a simple solution to segmenting objects within an image that have different coloration or grayscale values. As an example we use thresholding to separate the dark charcoal particles and count the pixels of these particles after segmentation. Continue reading “Quantifying Charcoal in Microscope Images Using MATLAB, Part 2”

Adaptive Filters in Paleoclimatology – the Python Version

Paleoclimate time series are often very noisy due to the combined effect of low sedimentation rates, intensive bioturbation and small sample sizes (5-20 foraminifers). Adaptive filters may help to increase the signal-to-noise ratio of such time series where conventional methods such as fixed filters cannot be applied if optimal filtering is to be achieved, because the signal-to-noise ratio is unknown and varies with time. Continue reading “Adaptive Filters in Paleoclimatology – the Python Version”

56th Online Shortcourse on MATLAB & Python Recipes for Earth Sciences

The popular online course on data analysis in the geosciences will be taught bilingual for the first time, using the two leading programming languages and development environments MATLAB and Python in parallel on 18–22 September 2023. The course is based on the 5th edition of my books MATLAB Recipes for Earth Science (Springer 2021) and Python Recipes for Earth Sciences (Springer 2022).

Continue reading “56th Online Shortcourse on MATLAB & Python Recipes for Earth Sciences”