Alyssa Heggison

I’m a student with the volcanology team at Sheffield and started in 2024 after completing a mathematics degree in Scotland. I’m focussing on the development of easy-to-use camera processing software for remote sensing of volcanic gas plumes. The project involves applying lots of areas of maths that I enjoyed studying at university, including image processing, machine learning and algorithm development, while learning about current research in volcanology which is completely new to me!

Automated Analysis of Volcano Imagery with Machine Learning Techniques

Reliable measurements of the rate at which gas is released in a volcanic plume are extremely beneficial for monitoring, research and hazard-asessment. Over the past decade the volcanology group at Sheffield have developed low-energy-use, low-cost UV Cameras for measurement of sulfur dioxide, which have already been installed at multiple locations and are returning image data. The main aim of this project is to automate the processing of the huge amounts of data returned, making real-time monitoring using the group’s cameras more practical. I’ll also focus on quantifying the uncertainty in estimated gas emission rates so that users are informed about the reliability of calculated data. By combining existing image processing techniques with computer vision and machine learning algorithms, I aim to automate the procedure in a way that is useable and explainable. I hope for this to contribute to the wider use of similar camera and processing systems, increasing the availability of SO2 flux data for researchers.

Supervisors: Dr Thomas Wilkes, Dr Tom Pering, Dr Jefersson Alex dos Santos