Ellen Bowler
Machine Learning Research Scientist
Biography
I’m a machine learning researcher based in the Artificial Intelligence (AI) lab at BAS. My research focuses on using machine learning to monitor and detect wildlife, particularly using satellite and drone imagery. I work closely with the Wildlife from Space research group, developing image algorithms to automatically count wildlife in very high resolution satellite imagery. For my PhD I developed a convolutional neural network to detect wandering albatrosses in 31-cm resolution WorldView-3 imagery – work which is being extended on in the Darwin Plus Albatrosses from Space project. Since joining BAS i have been involved with the Walrus from Space research, detecting walrus haulouts using lower resolution Sentinel-2 imagery. I am also involved with a WWF funded project using IceNet sea ice forecasts to predict risks to arctic wildlife. In this we are using GPS collar data to establish links between sea ice conditions and the timing and location of caribou migrations in the Coronation Gulf, to develop a Conservation Early Warning and Alert System which can inform local ecologists.
Research interests
Collaborations
Publications from NERC Open Research Archive
2024
Attard, Marie R.G. ORCID record for Marie R.G. Attard, Phillips, Richard A., Bowler, Ellen, Clarke, Penny J. ORCID record for Penny J. Clarke, Cubaynes, Hannah ORCID record for Hannah Cubaynes, Johnston, David W., Fretwell, Peter T. ORCID record for Peter T. Fretwell. (2024) Review of Satellite Remote Sensing and Unoccupied Aircraft Systems for Counting Wildlife on Land. Remote Sensing, 16. 23 pp. 10.3390/rs16040627
- AI for Earth Observation
- South Georgia seabirds from space
- AI for smart conservation
- Digital Twins of the Polar Regions
- Albatrosses from Space
- IceNet