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LiDAR EFI for growth projections: new approaches

OB 4a
Hub: Romeo Malette, ON
Year: 2022-2024
José Riofrío , PDF

Given that most actively managed stands within the Hub sites already have undertaken EFI programs, it is critical that lidar-dervied, static layers of key forest attributes are linked to regional growth and yield models. We recognise different models exist across Canada, with differing levels of fusion with lidar inventories. José will take existing research and examine a variety of model approaches including MIST in ON, and Natura in QB with the objective of producing models than can integrate lidar data and produce growth estimates at the management unit scale. To achieve this, we will first develop an overarching philosophy of model integration, and then implement and verify model predictions at Hub sites. Outcome (OB.4a): New approaches to integrate lidar EFI estimates into growth projections for broad implementation.

José Riofrío, PDF at University of British Columbia
Main Partner: Ministry of Natural Resources and Forestry (Ontario)
Professor Nicholas Coops & Alexis Achim

Riofrio, J., White, J.C., Tompalski, P., Coops, N., Wulder, M.A (2022) Harmonizing multi-temporal airborne laser scanning point clouds to derive periodic annual height increments in temperate mixedwood forests. Canadian Journal of Forest Research, 52(10):

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