Symposium Program

Early Detection of Woody Plant Expansion in Canadian Prairie Based on Drone Imagery and Deep Learning

Y. Pu, X. Lu, I. Soubry, Dr. X. Guo

University of Saskatchewan, Canada

Multi-Source Earth Observation Analysis in Canadian Grasslands: Enhancing Woody Plant Encroachment Detection & Benefits to the Environment and Economy

Dr. I. Soubry¹, Dr. L. N. Maros², Dr. X. Guo¹, Dr. R. S. Gray², Dr. E. Lamb³

¹Department of Geography and Planning, University of Saskatchewan, Canada; ²Department of Agricultural & Resource Economics, University of Saskatchewan, Canada; ³Department of Plant Sciences, University of Saskatchewan, Canada

Remote Sensing-Based Quantification and Mapping of Native Tree Cover in Saskatchewan’s Prairie Landscape

Dr. E. Shafeian¹, Dr. B. J. Mood¹, Dr. K. W. Belcher², Dr. C. P. Laroque¹

¹Mistik Askiwin Dendrochronology Laboratory, Department of Soil Science, University of Saskatchewan, Saskatoon, Canada; ²Department of Agricultural and Resource Economics, University of Saskatchewan, Saskatoon, Canada

Multi-Year Multitemporal Sentinel-1 and Sentinel-2 Imagery for Native Grassland and Seeded Forage Identification Across a Gradient of Southern Alberta Prairie Ecoregions

Dr. E. J. Lindsay¹, Dr. C. Champagne¹, B. Houston², Dr. B. Daneshfar¹, Dr. S. Mitchell³

¹Agriculture and Agri-Food Canada, Canada, Ottawa, ON; ²Agriculture and Agri-Food Canada, Canada, Regina, SK; ³Carleton University, Department of Geography and Environmental Studies

Machine learning models for improving subtropical forest biomass estimation using Sentinel-1/2 synergy

A. Aidoo Borsah¹, M. S. Wong^1,2, M. Nazeer¹, G. Shi^1,2

¹The Hong Kong Polytechnic University, Hong Kong S.A.R. (China); ²Research Institute for Land and Space, The Hong Kong Polytechnic University, Hong Kong, China