Summary. P-wave azimuthal seismic anisotropy of the uppermost mantle has been shown to indicate directions of extension, both recent and fossil, in oceanic and

Python Geoscience Modelling and Interpretation (PyGMI) is an open-source software development project, working with a GUI, programmed in Python. The main aim of PyGMI is to provide a free geoscientific tool for processing, interpretation and modelling of geoscience data, including magnetic, gravity and remote sensing data. It also allows for research into better ways to process, analyse and model data and as such is continually updated to implement these advances. Although is was originally intended to create voxel based three dimensional potential field models, it expanded to include tools for the processing and visualisation of raster data, import and visualisation of vector data (normally collected in surveys along lines), unsupervised and supervised cluster analysis, gravity processing, remote sensing processing and quality control tools for earthquake seismology. It is therefore a toolbox of numerous techniques to accomplish this. Examples of use include modelling of this Bushveld Igneous Complex (Cole et al., 2021) and remote sensing in the Namaqualand region, South Africa (Musekiwa, 2023).

The large number of remote-sensing datasets available necessitates the development of efficient methods when assessing change between such data. A series of techniques, optimizing the analysis of change detection, specifically on large remote-sensing dataset collections, is demonstrated. Iterative (online) statistical measures for mean and standard deviation give the ability to gain a measure of change over potentially hundreds of datasets without excessive computing power being needed. From this, the coefficient of variation can be used to provide further insight. Using such measures, seasonal change can be detected on outcrop (as opposed to vegetation), illustrating that change detection can be used to further extend a spectral signature for rocks. Twelve Sentinel-2 scenes over a 3 year period were used in this study. Thematic collection: This article is part of the Remote sensing for site investigations on Earth and other planets collection available at: https://www.lyellcollection.org/cc/remote-sensing-for-site-investigations-on-earth-and-other-planets

Remote sensing study of soil hazards for Odendaalsrus in the Free State Province