Using airborne LiDAR to quantify changes in forest structure following an ice storm disturbance and subsequent salvage logging

Ice storms are common disturbance agents in temperate forests, often causing complex damage by partially destroying tree crowns. These irregular damage patterns pose challenges in production forests. Post-disturbance management decisions, such as salvage logging, are typically based on hastily collected field data, which is costly, time-consuming, and often fails to capture damage heterogeneity. Remote sensing offers a practical alternative. In 2014, a severe ice storm damaged mixed forests across the northern Dinaric Mountains. We used multitemporal high-density Airborne Laser Scanning data to validate a procedure for quantifying ice storm damage in stands dominated by Norway spruce, silver fir and European beech, using field data as a reference. LiDAR-derived leaf area density profiles and voxel-based biomass loss estimates effectively reflected field-observed patterns. Methods based on individual-tree segmentation underestimated post-disturbance tree density reductions, but basal area and volume loss estimates aligned closely with field measurements, even at low point densities. These methods offer a scalable approach to damage assessment and improve understanding of the spatial variability of ice storm impacts. They also hold considerable promise for land managers with access to regional bitemporal LiDAR datasets.