Rylan Boothman

PhD Student, Natural Resource Sciences

Research Interests: machine learning, remote sensing, land use and land cover change, forest monitoring, TensorFlow, Google Earth Engine

Deforestation and forest degradation account for a large portion of annual global greenhouse gas emissions and are significant sources of biodiversity loss. Better analysis of the available satellite data archives could improve decision-makers' understanding and management of human impacts on forest changes. To this end, my research focuses on applying state-of-the-art machine learning techniques to extract more information than was previously possible from remotely sensed data. Before coming to McGill, I received a BSc in Computer Science from the University of Victoria.