Speaker
Description
Harvester-mounted mobile laser scanning (HarvMLS) is a novel approach to quantify forest structure in situ during harvesting operations. However, its reliability relative to established aerial- and ground-based laser scanning systems remains unknown. In this study, we quantified forest structure, assessed structural changes caused by thinning, and benchmarked HarvMLS against drone-based laser scanning (DLS) and handheld mobile laser scanning (HMLS). Point cloud data were collected in a boreal forest in southern Finland during thinning operations in 2024. Forty 10 × 10 m plots were processed using a grid-level approach. Forest structure was characterised using structural attributes (specifically maximum canopy height, mean canopy height, canopy cover (CC) and filled voxel proportion) and the coefficient of variation (CV) of the structural attributes. Results showed that thinning induced consistent structural changes across all three laser systems, which included a minor reduction in maximum canopy height, a moderate decline in mean canopy height, increased canopy openness and reduced filled voxel proportion. Increased CV values across attributes indicated greater heterogeneity post-thinning. No significant differences were observed between the scanning systems in estimating maximum canopy height, mean canopy height, CC or in their associated CV values. While significant differences were detected for filled voxel proportion; post hoc tests indicated no statistically significant difference between HarvMLS and HMLS. All systems consistently estimated the CV value of filled voxel proportion. These results demonstrate that HarvMLS provides reliable estimates of forest structural attributes and their variability during active forest operations.
| Keywords | biodiversity; complexity; wood harvesting |
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