<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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 (<italic>Quercus</italic> 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.</p></abstract>

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.

Allocation of oaks to Kraft classes based on linear and nonlinear kernel discriminant variables

Department of Mathematical and Statistical Methods, Poznań University of Life Sciences. Wojska Polskiego 28, 60-637 Poznań, Poland

Department of Forest Management, Poznań University of Life Sciences, Wojska Polskiego 71c, 60-625 Poznań, Poland

Biometrical Letters

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A method of discriminant variable determination was used to visualize the division of oak trees into Kraft classes. Usual discriminant variables and several...

Allocation of oaks to Kraft classes based on linear and nonlinear kernel discriminant variables

Published Online: Jun 08, 2016

Page range: 37 - 46

DOI: https://doi.org/10.1515/bile-2016-0005

Keywords
discriminant variables, kernel, Kraft classes, oak ( L.)

© 2016 Bogna Zawieja et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Allocation of oaks to Kraft classes based on linear and nonlinear kernel discriminant variables

Published Online: Jun 08, 2016

Page range: 37 - 46

DOI: https://doi.org/10.1515/bile-2016-0005

Keywordsdiscriminant variables, kernel, Kraft classes, oak ( L.)

© 2016 Bogna Zawieja et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
discriminant variables, kernel, Kraft classes, oak ( L.)