MSc of 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.

In my Computational Landscape Ecology laboratory, we are developing a diversified and innovative research program that focuses on answering environmental questions across large areas using a wide variety of approaches
including GIS, remote sensing, image interpretation, and cutting-edge techniques in computer science.

I am current doing projects in several scientific disciplines, including:

(1) the development and interpretation of a forest connectivity dataset for all of Canada; 

(2) the adaptation of a major new computer science algorithm for use in ecology;

(3) developing a new algorithm for updating land-cover classifications capable of ingesting data from multiple sensors of varying quality and specifications; and

 (4) the extraction of lake carbon content from satellite imagery of northern-hemisphere lakes.