%0 Research article
%T A decision support system for selective cleaning
%A Vestlund, Karin
%A Nordfjell, Tomas
%A Eliasson, Lars
%A Karlsson, Anders
%D 2006
%J Silva Fennica
%V 40
%N 2
%R doi:10.14214/sf.343
%U https://silvafennica.fi/article/343
%X Cleaning (pre-commercial thinning) costs have increased relative to  logging and regeneration costs, creating a desire for rationalisation.  Cleaning with robots may be a solution, but automating stem selections  requires a decision support system (DSS) capable of rendering acceptable  results. The aims were to develop a DSS for automation of individual  stem selections in practical cleaning, and to test, using simulations,  if it renders acceptable results. Data on 17 young forest stands were  used to develop a DSS that selects stems by species, position (including  distance and density parameters), diameter, and damage. Six simulations  were run, following the DSS, with different target settings for  density, percentage of deciduous stems and minimum distance between  stems. The results depend on the initial state of the stands, but  generally met the requested targets in an acceptable way. On average,  the density results deviated by –20% to +6% from the target values, the  amount of deciduous stems shifted towards the target values, and the  proportion of stems with defined damaged decreased from initially 14–90%  to 4–13%. The mean diameter at breast height increased and the minimum  allowed distance between stems was never violated. The simulation  results indicate that the DSS is operational. However, for  implementation in robotics a crucial problem is to automatically  perceive the selected attributes, so additional simulations with  erroneous data were run. Correct measurements of diameters are less  crucial than to find the majority of the trees and the majority of trees  with damages.