Estimation of Forest Structure and Fuel Change Across Mountain Pine Beetle – Attacked Forests Using Mobile and RPAS – Based LiDAR - Evan C. Gerbrecht; Nicholas C. Coops; Allan L. Carroll; Christopher W. Bater; Leonard Buechner (Canadian Journal of Remote Sensing)
The recent mountain pine beetle (Dendroctonus ponderosae) outbreak has resulted in widespread mortality of pine trees across western Canada over the past two decades. The changes to forest structure caused by the beetle are well known through ground-based observations. However, the potential changes to fuels for wildfires associated with altered forest structure are not well known nor incorporated into fire fuel models. In this study, we used light detection and ranging (LiDAR) to quantify variations in forest structure and wildfire fuels caused by mountain pine beetle (MPB) infestation. From this data, we created models that characterize fuels following MPB attack. LiDAR metrics were extracted from three-dimensional point clouds acquired using remotely piloted aircraft systems (RPAS) and mobile laser scanning (MLS), both individually and combined. Fuel components in the stand were then modeled across a range of MPB attack severities. Results indicated the fused model was most accurate at predicting canopy fuel load (R2 = 0.80), while MLS had the best model performance for shrub fuel load (R2 = 0.68) and coarse woody debris fuel load (R2 = 0.68). This study demonstrates the ability of LiDAR to accurately characterize forest fuel loads in MPB-infested forests.