Management and monitoring of mid-rotation stands with tree-level remote sensing approaches

Canada's forests face escalating losses from insect outbreaks, wildfires, and shifting growing conditions. These disturbances, together with social and land-base constraints on primary forests, are accelerating the transition toward a timber supply based on stands regenerated after harvest. Ensuring these stands develop into productive, resilient forests under climatic uncertainty requires monitoring and silvicultural intervention throughout the mid-rotation. Favouring tree species mixtures can improve growth and resilience to disturbance, while thinning redistributes growth to retained stems and provides immediate timber to mitigate supply shortages. Implementing these approaches requires spatially explicit, tree-level information that conventional aerial photography and plot-based monitoring do not provide. This dissertation examines how tree-level inventories derived from airborne laser scanning can address these needs across two forest tenures: a boreal managed forest in Ontario and coniferous stands managed for commercial thinning in interior British Columbia, Canada, using acquisitions spanning wide-area single-photon lidar to high-density drone laser scanning. Across four chapters, I evaluate vertical structure characterization with single-photon lidar, finding general agreement with a conventional lidar reference. I then combine multitemporal single-photon acquisitions with an unmanned aerial vehicle laser scanning reference to resolve species-specific height growth in regenerating mixtures, revealing differences linked to shade tolerance. Turning to commercial thinning, I link tree-level laser scanning with dendrochronological growth records in British Columbia, where crown volume predicts 70% of the variation in five-year basal area growth, and synthesize a growth competition priority index mapping where competition may strongly suppress growth. Finally, I integrate tree-level observations with a spatially explicit growth model in a framework that assesses commercial thinning and projects treated stands to rotation maturity. Applied across 295 ha of thinned stands, this framework projects on average 49% greater large log volume (greater than 40 cm diameter) by age 80 compared to unthinned simulations. These inventories allow managers to compare development trajectories across species mixtures and between thinned and unthinned stands, evaluating alternative silvicultural choices directly from observations. Together, these chapters show that tree-level airborne laser scanning inventories are a foundational geospatial technology for managing Canada's post-harvest forests toward productivity and resilience under changing climate and disturbance regimes.