This work presents simulations, modelling, and experimental verification of a novel steady-state surface nuclear magnetic resonance (NMR) transmitter used for the non-invasive exploration of groundwater. The paper focuses on three main aspects of high-current transmitter instrumentation: thermal management, current-drooping, and pulse stability. This work will interest readers involved in geoscientific instrument prototyping for groundwater exploration using portable geoscientific instruments.

In the field of marine controlled-source electromagnetic (MCSEM) systems, the evident issue of heating caused by the demand for high power was observed during previous marine experiments, where devices and cables were damaged due to overheating. Therefore, the idea was conceived to design a non-contact temperature measurement system tailored specifically to MCSEM systems, with the capacity to seamlessly adapt to the existing hardware conditions at sea.

The Modular Aquatic Robotic Platform–Freiberg (MARP-FG) is an autonomous catamaran designed to improve water monitoring by reducing human-related biases. It supports customizable sensors for water profiling, 3D basin mapping, and greenhouse gas flux measurements. Tested in Amazonian and European waters, MARP-FG showed precise navigation and reliable data collection under challenging weather, enhancing long-term, automated aquatic ecosystem monitoring.

The Quantum Geographic Information System (QGIS) Sentinel Vegetation Indices (QSVI) plugin is an efficient, user-friendly tool designed to calculate key environmental remote sensing indices. Developed using a Python library within the QGIS software, QSVI significantly reduces computation time, exceeding other popular GIS applications. This study demonstrates its effectiveness in processing large datasets, offering a cost-effective solution for environmental monitoring and analysis, which is particularly valuable in educational settings.

We constructed an easy-to-use, open-source method for mapping minerals in rock thin sections. We implemented the method within the geographical information system QGIS and the Orfeo ToolBox plugin using random forest image classification on scanning electron microscope data. We applied the method to 14 rock thin sections. Mineral abundance estimates from our method compare favorably to previously published estimates, and 96 % spatially and categorically agree with manually derived mineral maps.