Karin Vestlund, Tomas Nordfjell, Lars Eliasson, Anders Karlsson. (2006). A decision support system for selective cleaning. Silva Fennica vol. 40 no. 2 article id 343. https://doi.org/10.14214/sf.343

Keywords: forestry; pre-commercial thinning; automation; practical cleaning

Abstract | View details | Full text in PDF | Author Info

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.

Vestlund, Swedish University of Agricultural Sciences, Department of Silviculture, P.O. Box 7060, SE-750 07 Uppsala, Sweden E-mail: karin.vestlund@ssko.slu.se
Nordfjell, Swedish University of Agricultural Sciences, Department of Forest Resource Management and Geomatics, SE-901 83 Umeå, Sweden E-mail: tn@nn.se
Eliasson, Swedish University of Agricultural Sciences, Department of Silviculture, SE-901 83 Umeå, Sweden E-mail: le@nn.se
Karlsson, Swedish University of Agricultural Sciences, Department of Silviculture, SE-901 83 Umeå, Sweden E-mail: ak@nn.se

article id 363, category Research article

Karin Vestlund, Tomas Nordfjell, Lars Eliasson. (2005). Comparison of human and computer-based selective cleaning. Silva Fennica vol. 39 no. 4 article id 363. https://doi.org/10.14214/sf.363

Keywords: forestry; decision support; pre-commercial thinning; automation; practical cleaning; training-tool

Abstract | View details | Full text in PDF | Author Info

In silvicultural tending operations like cleaning (pre-commercial thinning), the results are irreversible, so it is important for the decisions to be consistent with the aims for the stand. To enable operational automatic stem selections, a decision support system (DSS) is needed. A previously presented DSS seems to render acceptable cleaning results, but needs further analysis. The aims of the study were to compare the cleaning results of experienced cleaners and DSS simulations when “similar” instructions were given, and to assess the usefulness and robustness of the DSS. Twelve experienced cleaners were engaged to “clean” (mark main stems) six areas; each cleaner “cleaned” two areas. The DSS was used to generate two computer-based cleanings (simulations) of these areas. Four laymen also “cleaned” one of the areas following the DSS. The density results were significantly affected by the areas’ location, whereas the proportions of deciduous stems and damaged stems were significantly affected by both the areas’ location and method, i.e. manual “cleaning” and general or adjusted simulation. The study showed that the DSS can be adjusted so that the results are comparable with the cleaners’ results. Thus, the DSS seems to be useful and flexible. The laymen’s results were close to the results of the “general” simulation, implying that the DSS is robust and could be used as a training tool for inexperienced cleaners. The DSS was also acceptable on a single-tree level, as more than 80% of the main-stems selected in the simulations were also selected by at least one cleaner.

Vestlund, Swedish University of Agricultural Sciences, Department of Silviculture, P.O. Box 7060, SE-750 07 Uppsala, Sweden E-mail: karin.vestlund@ssko.slu.se
Nordfjell, Swedish University of Agricultural Sciences, Department of Silviculture, SE-901 83 Umeå, Sweden E-mail: tm@nn.se
Eliasson, Swedish University of Agricultural Sciences, Department of Silviculture, SE-901 83 Umeå, Sweden E-mail: le@nn.se

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