T: 514-398-7902 | jeffrey.cardille [at] mcgill.ca (Email) | Macdonald-Stewart Building, MS2-078 | Website
PhD (University of Wisconsin)
MSc (University of Wisconsin)
MSc (Georgia Institute of Technology)
BSc (Carnegie Mellon University)
Jeff is a professor at McGill University who studies land-cover change, forest connectivity, and lake carbon content. He likes trying to answer large environmental questions at regional, continental, and global scales using a wide variety of approaches, including simulation modeling, remote sensing, GIS, supercomputing, and cutting-edge techniques in computer science. As a teacher, he has taught hundreds of students about geographic information systems at McGill for several years and before that, taught students about les systèmes d’information géographique at the Université de Montréal. Born in Pennsylvania, Jeff graduated from the well-regarded computer science program at Carnegie Mellon in Pittsburgh. After several years in the private sector at Bell Communications Research, he left the corporate world for graduate school, where he earned two M.S. degrees, with a Ph.D. from the University of Wisconsin-Madison. For his Ph.D. research he created one of the first maps of agriculture and pasture use across the entire Amazon basin, then developed a model of water and carbon cycling across 7000 lakes in Northern Wisconsin for his postdoc at UW-Madison’s Center for Limnology. He recently developed a method for analyzing forest connectivity across all of Canada, and is working on regional and global models of land-cover change across the entire 40-year satellite record in collaboration with Google’s powerful Earth Engine platform.
With the dramatic increase in availability and accessibility of spatial data through advances in remote sensing and GIS, virtual globes, and computing power, coming decades will reward research that uses these revolutionary new ways of viewing, interpreting, and forecasting changes in environmental systems. Using a wide array of approaches, I explore the impact of abiotic, biotic, and human factors on spatial patterns at multiple scales. My research focuses on both basic and applied questions of environmental change across large areas, paying particular attention to issues having an explicit spatial component. My group’s research addresses several disciplines, including landscape ecology, remote sensing, and data handling and visualization.
(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.