Optimal bucking of stems from terrestrial laser scanning data to maximize forest value

Abstract

An optimal bucking strategy that allocates cutting patterns to forest stands based on the individual characteristics of each stem is critical for maximizing value recovery. However, cutting patterns are usually excluded from bucking algorithms due to the difficulties associated with capturing tree quality features when collecting forest inventory data (e.g. branchiness and tree shape). This paper presents a non-destructive and fully automated methodology for the optimal bucking of stems based on terrestrial laser scanning (TLS) point clouds that aims to maximize the economic value of trees in a forest stand. It is based on the three-dimensional modelling of stems and includes the diameter and curvature of each log. The bucking algorithm also considers several timber products and calculates the most valuable log combination for each tree. The methodology was tested in a Pinus radiata plot with 120 trees, and the results were compared with those obtained with input data that do not take curvature into account: i.e. only diameters from TLS and taper equations. The analysis of the results suggests that not including curvature in the algorithm for optimal bucking results in an overestimation of the commercial value of timber products.