Summer 2023
Project title: Exploring plume dynamics in the La Soufrière St Vincent eruptions of April 2021
Supervisors: Dr. Isabelle Taylor, Prof. Don Grainger, Prof. David Pyle (University of Oxford)
Name of internship student: Geri Peykova
Bio: In 2020 I started my Bachelor’s degree in Natural Sciences at the University of Cambridge , with the intention to specialize in Physics. During my coursework, I took several geology classes, and really liked their observational approach and all the exciting field trips across the UK. This is when my fascination with volcanoes started too, especially after witnessing the 2021 eruption of Fagradalsfjall in Iceland. In the summer of 2022, I combined my love for the outdoors, travel and geology and organized a mapping expedition to the High Himalayas in Ladakh, India, at 4000m, along with two friends. For my Master’s degree at Cambridge, I am shifting my focus slightly to delve into Astrophysics, complementing my existing geology knowledge with planetary science courses. Currently, my academic goals include exploring computational modelling of planetary processes and joining a research expedition to Antarctica.
Project: The 2021 eruption of La Soufriere volcano on the island of St Vincent consisted of a series of eruptive events occurring over 14 days. This project focuses on understanding the dynamics
of the ash plumes of the different events during this period and determining the ascent rates by accurately estimating plume heights. A novel method based on the observation of waves within the plume was developed. This method uses 1-minute resolution satellite imagery from the Advanced Baseline Imager (ABI) on board the GOES-East Satellite to track the evolution of the volcanic plume during each event. By analyzing the formation of buoyancy waves and the ambient conditions, the plume heights during multiple events were estimated and compared to heights obtained through other methods. The insights gained from this analysis contribute to our understanding of volcanic eruption dynamics and hazard management.
Outputs: A new method for estimating the height of volcanic ash plumes by analyzing the formation of waves within them was developed. One of the advantages of this method is that it provides a single solution for plumes near the tropopause, where one of the most common methods that uses the brightness temperature usually produces two possible solutions. Moreover, it is not limited to daylight observation as direct imaging is. The method was applied to a range of events from the 2021 La Soufriere eruption and the results closely matched height estimates obtained through other methods. Accurate height estimates allowed ascent rates to be calculated as well. Further testing of this method is necessary, both for events from the La Soufriere eruption and, when data is available, in other volcanic eruptions.
The findings of the project were summarized in a report, published on the EODG website. Additionally, I presented my work at one of the group meetings in front of the research group and other members of the Physics and Earth Sciences departments and the COMET Student meeting in January 2024 at the University of Leeds.
Click here to read Geri’s blogpost on detailed methods to measure volcanic plume heights.
The overall experience: I enjoyed my internship as it gave me a taste of what research is like. I really liked the open-ended nature of my project, giving me the freedom to try different things before deciding on the direction I wanted to take. The whole experience allowed me to apply and enhance my coding skills and taught me how to work with satellite data, which I think will be very handy in the future.
My research group was incredibly supportive and always ready to help and created a friendly working environment. I really appreciate it that I got to do a presentation in front of the group and other members of the department as it was a great learning experience.
Overall, I’m grateful for the experience and knowledge I’ve gained through this internship.
Summer 2022
Project title: Improving Building Exposure Datasets using High-Res Imagery and Deep Learning
Supervisors: Dr. Scott Watson and Dr. John Elliott (University of Leeds)
Name of internship student: Francesca (Frankie) Butler
Bio: Final Year Undergraduate at the University of Aberdeen, reading Geology and Petroleum Geology, with a specific interest in pursuing a PhD in Volcanology, Magma Mixing.
Following a life changing injury, I have had to look deeper at remote Geology, attend virtual field trips, GIS Mapping and most recently, the new frontier of Deep Learning in GIS.
I am also interested in science communication, and I am part of the Geoscience academic community on Twitter – @frankiealoise I enjoy presenting ideas/research and documenting my journey as a disabled geologist, both in the field and the lab.
I thoroughly enjoyed the COMET internship as it gave me the opportunity to learn new skills and speak at the annual student COMET meeting, combining PhD style research with Science communication and remote Geology/ Geoscience work!
Project:
Project title: ‘Improving Building Exposure Datasets using High-res Imagery and Deep Learning’
Testing the application of a variety of deep learning models to an area of Kathmandu and assessing transferability and improvements
Independent 6-week summer research project, fully funded by NERC, COMET and the University of Leeds.
Manually mapping buildings in Kathmandu, Nepal from high resolution satellite imagery. Using QGIS and ARCGIS to draw polygonal outlines around buildings.
These manually collected outlines were then used to train Deep Learning Models to identify buildings with the end goal to create a pre-trained Deep Learning model for Kathmandu. Investigated the use of Non-Differentiated Vegetation Index (NDVI) masks to improve the accuracy assessment score and improve the overall accuracy of the model.
These deep learning models are important for mapping building footprints quickly. Kathmandu currently has no established model and this will help to inform future planning and humanitarian response following natural disasters.
Outputs:
Partially trained Deep Learning Models for Kathmandu.
Accuracy Assessment Scores for Pre-trained deep learning models.
Helped to define a direction for future research for my Supervisor Dr Scott Watson; the use of Non-Differentiated Vegetation Index (NDVI).
15 Minute presentation at the NERC COMET student meeting in person in Manchester (January 15th 2023)
The overall experience:
I thoroughly enjoyed the NERC summer internship programme.
I learnt so much about the process and approach you must have to research projects.
I felt I was learning and contributing to research at the forefront of the field.
Deep Learning programmes are becoming more prevalent within Geoscience, the work I did with Scott has helped me throughout my current Geology degree. I have attended PhD and Post-Doc talks on Deep Learning, and I understood their approach and felt I could ask relevant questions.
Scott was an excellent supervisor, I had enough free reign to investigate areas I felt
needed investigating, but I also had enough guidance. I felt I could ask any questions without fear of retribution.
I learnt how to use some incredibly useful programmes that I am integrating into my own research.
It was interesting as the project was within an area of geoscience that I am not wholly comfortable with- coding and new programmes. But the process of learning how to use them, making mistakes and learning how to rectify them, was really important for my overall development as a scientist.
This project has helped to solidify that I would like to pursue a PhD in Geology.
I completed this project whilst recovering from a serious life-changing injury. The understanding and compassion from all staff members allowed me to complete the work to a high standard whilst not jeopardising my recovery.
I truly enjoyed the experience, thank you to Leeds and NERC for this experience!