A method of discriminant variable determination was used to visualize the division of oak trees into Kraft classes. Usual discriminant variables and several types of kernel discriminant variables were studied. For this purpose the traits of oak (Quercus L.) trees, measured on standing trees, were used. These traits included height of tree, breast height diameter and crown projection area. The use of the Gaussian kernel and modified Gaussian kernel enabled the clearest division into Kraft classes. In particular, the latter method proved to be the most effective.
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Annual height increments are a very important characteristic of Scots pine. They have a direct effect on the determination of the dendrometric properties of a stand, such as volume increment. In the present study the data concern height increments of the main shoot in selected age classes of trees (age 72 to 92 years). A relationship is determined between the values of the increments and meteorological conditions such as temperature, precipitation and sunshine. On the basis of lasso regression analysis, precipitation in the year preceding the incremental season was shown to have the greatest effect on height increments of Scots pine.
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