New generalized height-diameter models for birch in European Russia

Abstract

Height and diameter at breast height are basic variables that are measured in a forest inventory. Generalized models do not require measuring tree heights or number of measurements is minimal. The purpose of this study was to obtain 24 new generalized height-diameter models based on simple basic models, compare them with 9 generalized models selected from other studies, and develop an appropriate height-diameter model for birch in the European Russia. To select models which better describe the relationship between the heights and diameters of the trees, six metrics were used – root mean square error (RMSE), mean absolute percentage error (MAPE), coefficient of determination (R2), adjusted coefficient of determination (R2-adj.), Akaike information criterion (AIC) and Bayesian information criterion (BIC). Results show that there are slight differences between all models. The performance statistics showed that model M24 is the most suitable and recommended for predicting the height-diameter relationships for birch trees in this study area. The predicting variables for applying developed generalized models to estimate total tree height require less sampling effort and are derived from conventional forest inventory data which allows to reduce costs and time consumption in field work.