Overview and details of the sessions of the 45th Canadian Symposium on Remote Sensing. Please select a date or location to show only sessions at that day or location. Please select a single session for further details on the presentations. Once you select a session or choose the List View of the program, you can access the extended abstracts by clicking on the button "Show Downloads" . *** You should be logged into your ConfTool account to be able to see the downloadable items ***
Scientific Session 12: Application of Remote Sensing in Forestry
Time:
Thursday, 13/June/2024:
1:00pm - 2:40pm
Session Chair: Prof. Richard Fournier Session Chair: Dr. Karin Yvonne van Ewijk
Location:SUB 307
Presentations
1:00pm - 1:20pm
Integrating Spaceborne LiDAR GEDI and Multitemporal Optical and SAR Data with a Deep Learning Model to Map Forest Canopy Height in Ontario, Canada
Dr. J. D. Bermudez Castro1, Dr. C. Rogers2, Dr. C. Sother3, Dr. A. Gonsamo1
1McMaster University, Hamilton, ON, Canada; 2Toronto Metropolitan University, Toronto, ON, Canada; 3Planet Labs PBC, San Francisco, CA, USA
1:20pm - 1:40pm
Individual Tree Crown Delineation for Coniferous Trees Using StarDist Model
Dr. F. Tong, Prof. Y. Zhang
University of New Brunswick, Canada
1:40pm - 2:00pm
Tree Species Classification on Hyperspectral Imagery Using Fewer Training Samples
Dr. F. Tong, Y. Zhang
University of New Brunswick, Canada
2:00pm - 2:20pm
Direct Estimation of Forest Aboveground Biomass from UAV LiDAR Observations for a Red Pine Plantation in Southern Ontario
J. Chau1, K. So1, S. Rudd2, D. T. Robinson3, A. Gonsamo1
1School of Earth, Environment and Society, McMaster University, 1280 Main Street West, Hamilton, Ontario, L8S 4K1, Canada; 2Korotu Technology, 720 Bathurst Street, Toronto, Ontario, M5S 2R4, Canada; 3Department of Geography and Environmental Management, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, N2L 3G1, Canada
2:20pm - 2:40pm
Individual Tree Crown Detection and Delineation Using Mask R-CNN with LiDAR Data in a Mixed-Wood Forest
