A Modeling Approach to Estimating Skidding Costs of Individual Trees for Thinning Operations

Abstract

Abstract Thinning is a common silvicultural treatment used for different forest management purposes. Traditionally, thinning prescriptions are derived from sample plots and applied to stands with various vegetation conditions. A few studies have optimized cut-tree selection to create site-specific thinning prescriptions. However, these studies greatly simplify the estimation of harvesting costs by ignoring the location of the cut trees relative to the extraction point. Consequently, resulting tree-level thinning prescriptions might not provide the most economically efficient selection of cut trees. In this study, we developed a model to estimate skidding costs of individual cut trees based on size, location, and spatial distribution of selected cut trees. The model uses a log-bunching algorithm to identify log-pile locations and then creates a skid-trail network that connects log piles to the exit point at a minimum skidding cost. We applied the model to a treatment unit, where light detection and ranging data were used to obtain terrain and tree data, considering two thinning scenarios with target densities of 400 and 300 leave trees/ha, respectively. Comparison of the model results with those obtained from the existing cost models indicates that our model results are within a reasonable range for skidding costs. As our model considers terrain slope to create skid trails, it can be effectively used to delineate nonaccessible or difficult terrain areas for skidding operations. The model can also be used to automatically generate optimal skid-trail networks connecting multiple log piles to the exit point.