Current Lab Members
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Morgan A. Crowley
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PhD Candidate (Department of Natural Resource Sciences)
Research Interests: fire mapping, disturbance detection, Remote sensing, multi-source data synthesis, Landsat, Sentinel-2, MODIS, Google Earth Engine, Bayesian Updating of Land Cover algorithm Extreme fire seasons are becoming increasingly common across Canada, and annual burned area is predicted to escalate. Widespread and large fires impact ecosystem services such as timber supply, wildlife habitat, and carbon storage, and diminished air quality has a detrimental effect on human health and well-being. Accurate maps of active fire progression can help stakeholders fight fires, better understand how they burn, and model future landscape disturbance and subsequent impacts on ecosystem services. The primary objective of my thesis is to develop data fusion methods to produce and analyse decades of fire progressions at the provincial level. By using novel classification and data-fusion methods to refine burned-area mapping, this dataset and subsequent analyses hope to offer insights to the fields of fire ecology and disturbance monitoring. ResearchGate OrcID Google Scholar
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Elijah Perez
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MSc of Natural Resource Sciences
Eli completed his undergraduate degree at McGill University in Environmental Biology specializing in Wildlife Biology and is now a first year masters student in NRS. His remote sensing work, under the supervision of professor Jeff Cardille, allows him to blend his scientific and professional interests at the intersection of technology, Big Data, and the natural world. He hopes to improve the detection of forest disturbances in British Columbia with potential application Canada wide, helping to improve forest management. |
Talia Koll-Egyed
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MSc of Natural Resource Sciences
Research Interests: Lakes, Coloured dissolved organic matter, Secchi disk depth, Remote sensing, Landsat- 8, Sentinel-2, Google Earth Engine Canada is rich in freshwater resources, boasting approximately 20% of the global supply. These resources are under increasing human pressure, with climate change already impacting both the availability and quality of freshwater. Despite their importance in Canada, a national-scale accounting of lake water parameters has, until very recently, been impossible. With the large field effort of the NSERC Lake Pulse Strategic Network, hundreds of lakes have been sampled as the basis for a nationwide lake assessment. Yet with hundreds of thousands of never-sampled lakes to consider, satellite data provides the only viable means for extensive monitoring of these bodies of water. The primary objective of my thesis is to develop algorithms to predict the concentration of coloured dissolved organic matter and Secchi disk depth. This research will expand our knowledge of lake water quality parameters at a country-wide scale and provide a baseline estimate for carbon content in the lakes of Canada. |
Sara Pancheri
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Technician/Technologist (Environmental & Wildlife Management, Vanier College) Research Interests: Remote Sensing, MSS Landsat, Lake Mapping, BULC (Bayesian Updating of Land-Cover), GIS From Bird Banding and Insect Collections in the field to GIS and Microbiology in the lab, EWM technicians pride themselves in their flexibility and skill in careers related to the environment. My role in Dr. Cardille's lab is to assist his students and staff (from undergraduates to Ph.D candidates) with their research related to Computational Landscape Ecology. My current projects include MSS Imagery analysis & classification and global lake mapping. |
Africa Flores-Anderson
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PhD Student (Department of Natural Resource Sciences)
Research Interests: Land Use Land Cover Change (LCLUC), remote sensing, synthetic aperture radar (SAR), water quality, hyper spectral, forest monitoring, time series analysis, AI Tropical forests display very dynamic rates of change due to human intervention, with a trend towards forest loss. In the last decade technological advances have allowed scientists to map historical forest cover change globally using archives of satellite data. However, decision makers need national level estimations and understanding of more subtle forest disturbances to take appropriate measures to protect their forests. My research interest lies in the use of Earth observations from passive and active sensors to provide useful and timely information that will enable decision makers to enhance the management of their forest and water resources. I also work in monitoring and forecasting algae blooms in fresh-water bodies using satellite data and machine learning. I’m originally from Guatemala and hold a Bachelor’s Degree in Agricultural Engineering with focus in Natural Renewable Resources from Universidad de San Carlos in Guatemala, and a MSc in Earth System Science from the University of Alabama in Huntsville. ResearchGate
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Rylan Boothman
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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. |
