Integrating Remote Sensing and Simulation Modelling to Evaluate Corridor Thinning in Early Forest Management

Corridor thinning is a promising early forest management method aimed at improving harvesting productivity and enabling cost-effective biomass recovery from young and dense stands. Despite its operational advantages, quantitative comparisons with traditional selective thinning under realistic stand conditions are still limited. This study integrates UAV-based remote sensing, field measurements, and an agent-based simulation model to evaluate corridor thinning performance relative to selective thinning in first thinning operations. Field trials were conducted in Southern Savonia, Finland, where LiDAR and digital aerial photogrammetry (DAP) were used to reconstruct forest structure at single-tree level. Based on UAV-derived data, six virtual forest plots (50 × 20 m) were generated and imported into a simulation model representing harvester and crane operations. The model was parameterized and validated using time measurements from field demonstrations and complemented with harvester operator interviews. Simulation results indicate that corridor thinning achieves higher productivity than selective thinning, primarily due to shorter and more systematic crane movements within harvesting corridors. Operators reported that corridor thinning becomes intuitive after an initial adaptation phase and is especially suitable for overgrown stands, whereas selective or hybrid approaches were preferred when collecting multiple assortments. The results demonstrate that combining remote sensing and agent-based simulation provides an effective framework for evaluating thinning strategies and supporting data-driven planning in early forest management.