| Current methods for managing epidemic outbreaks of mountain pine beetle (MPB) rely in part on identifying forest stands that are most susceptible to attack. This work is presently performed using standard forest-inventory data such as the Alberta Vegetation Inventory (AVI) or the Vegetation Resource Inventory of British Columbia. However, these inventories typically lack full areal coverage, and often suffer from a variety of other quality issues that may impact their effectiveness. This research tested the capacity of modern remote-sensing instruments to measure MPB susceptibility, by comparing optical and LiDAR-based datasets with traditional AVI-based estimates across a 34,000 km2 study area in west-central Alberta. The remote-sensing data vastly enhanced the areal coverage of susceptibility estimates (from 9% coverage of the study area to 100%), and improved susceptibility accuracy from 35% (Kappa=0.11) to 87% (Kappa=0.66). |
