Automated selective thinning via multicriteria maetaheuristic procedure

Abstract

Forest thinning is an important forestry practice for regulating competition among individuals, as well as for reestablishing the growth of the remaining trees with greater potential for commercialization. However, the selection of individuals to be removed is a complex process which involves technicians skilled in the identification of various variables in the field and making the most appropriate decision. By means of this process one can obtain heterogeneous responses and the lack of technical team standardization may lead to prejudicial choices for forest management. Therefore, the aim of the study was applying a multi-criteria simulated annealing metaheuristic for the selection of trees to be removed in selective thinning, considering the diametric structure of the forest stand, height, canopy occupation, crown projected area and the tree quality. The study was conducted on a forest stand of Eucalyptus grandis containing 336 trees. Ten scenarios were simulated, covering different weights in the multi-criteria function to be minimized. The results show that the metaheuristic is capable of selecting individuals for selective thinning, presenting advantages such as improved standardization of choices using predetermined criteria, independent of the probability of selecting trees at the stand level. It was concluded that the use of the method will become more promising after using the efficient data acquirement technology, while always being a method for decision making.