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Airborne laser scanning (ALS) has recently gained increasing attention in forestry, as ALS data may facilitate the efficient assessment of forest inventory attributes and ecological indicators related to forest stand structure. This paper presents a novel workflow for individual tree detection and tree crown delineation using ALS data. The developed point-based approach included several tree allometry rules on permissible tree heights and crown dimensions to increase the likelihood of detecting the actual tree profiles. The accuracy of the method was assessed in a heterogeneous forest with a complex stand structure in Slovakia (Central Europe). ALS measurements were taken using a RIEGL Q680i scanner at 700 m of height with a point density of 20 echoes per m2. The ground reference data included the measured positions and dimensions of 1332 trees in nine plots distributed across the region. We found that the number of individual trees detected by the algorithm using ALS data was systematically underestimated by 34 ± 15% relative to the reference data. The delineated crown coverage was underestimated by 2 ± 6% as well, but the latter difference was not statistically significant (p>0.05).

Integration of tree allometry rules to treetops detection and tree crowns delineation using airborne lidar data