Jori Uusitalo, Anne Puustelli, Veli-Pekka Kivinen, Tapio Nummi, Bikas K. Sinha. (2006). Bayesian estimation of diameter distribution during harvesting. Silva Fennica vol. 40 no. 4 article id 321. https://doi.org/10.14214/sf.321

Keywords: diameter distribution; Bayesian statistics; tree harvesting

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This research aims to combine two different data sets with Bayesian statistics in order to predict the diameter distribution of trees at harvest. The parameters of prior distribution are derived from the forest management plans supplemented by additional ocular information. We derive the parameters for the sample data from the first trees harvested, and then create the posterior distribution within the Bayesian framework. We apply the standard normal distribution to construct diameter (dbh) distributions, although many other theoretical distributions have been proved better with dbh data available. The methodology developed is then tested on nine mature spruce (Picea abies) dominated stands, on which the normal distribution seems to work well in mature spruce stands. The tests indicate that prediction of diameter distribution for the whole stand based on the first trees harvested is not wise, since it tends to give inaccurate predictions. Combining the first trees harvested with prior information seems to increase the reliability of predictions.

Uusitalo, The Finnish Forest Research Institute, Parkano unit, FI-39700 Parkano, Finland E-mail: jori.uusitalo@metla.fi
Puustelli, University of Tampere, Department of Mathematics, Statistics and Philosophy, FI-33014 University of Tampere, Finland E-mail: ap@nn.fi
Kivinen, University of Helsinki, Department of Forest Resource Management, Box 27, FI-00014 University of Helsinki, Finland E-mail: vpk@nn.fi
Nummi, University of Tampere, Department of Mathematics, Statistics and Philosophy, FI-33014 University of Tampere, Finland E-mail: tn@nn.fi
Sinha, Stat-Math Division, Indian Statistical Institute, 203 B.T. Road, Kolkata - 700 108, India E-mail: bks@nn.in

article id 417, category Research article

Jori Uusitalo, Sampsa Kokko, Veli-Pekka Kivinen. (2004). The effect of two bucking methods on Scots pine lumber quality. Silva Fennica vol. 38 no. 3 article id 417. https://doi.org/10.14214/sf.417

Keywords: harvesting; mechanized logging; tree bucking

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

Modern harvesters are equipped with measurement and bucking optimization systems able not only to continuously measure the length and diameter of the stem but also to predict the profile of the unknown part of a stem and to calculate the optimal cross-cutting points for the whole stem. So far, tree-bucking optimization in the Nordic countries has been efficiently applied only with spruce because the quality of pine and birch varies much more both within a stem and between stems. Since limitations in the measuring equipment mean that the presence and position of grade limits as well as additional defects in the stem will normally have to be detected and estimated manually. Consequently, optimization works inefficiently because the harvester operator is continuously forced to disregard the cutting suggestions supplied by the harvester’s automatic system. This paper presents the outcome of research intended to define how change from the current quality bucking principle to automatic bucking affects lumber quality. The study is based on field experiments and test sawing data on 100 Scots pine (Pinus sylvestris) stems from southwestern Finland in 2001. Automatic bucking does not markedly lower the amount of good-quality lumber compared to quality bucking. Since automatic bucking inevitably leads to log distribution that matches the length requirements of customers better, it may be regarded as appropriate for these harvesting conditions.

Uusitalo, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: jori.uusitalo@joensuu.fi
Kokko, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: sk@nn.fi
Kivinen, University of Helsinki, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: vpk@nn.fi

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