Automated detection of individual trees from airborne LiDAR point clouds over Malcolm Knapp Research Forest using the Li et al. (2012) point-cloud algorithm and the Dalponte & Coomes (2016) CHM-based algorithm, with resolution sensitivity analysis.
A Python-based Random Forest workflow to predict dominant tree species at the stand level in the Petawawa Research Forest using ALS-derived structural metrics, topographic variables, and Landsat 8 multispectral bands. Demonstrates the accuracy gain from fusing LiDAR with spectral data.
A collection of GIS-based cartographic works including salmon habitat modelling, daycare network analysis, object-based land cover classification, wildlife connectivity mapping, and more.