Generalized height-diameter models for Picea orientalis L.

Area of Science:

• Forestry
• Ecology
• Biometrics

Background:

• Accurate tree height estimation is crucial for forest inventory and management.
• Stand and individual tree variables are commonly used in height-diameter models.
• Picea orientalis (Oriental spruce) is an important timber species in northeastern Turkey.

Purpose of the Study:

• To compare the performance of major non-linear models for estimating the height of Picea orientalis L. trees.
• To identify the best-performing model for height estimation based on individual tree diameter and stand variables.

Main Methods:

• Data were collected from 440 Picea orientalis trees in pure, even-aged stands near Artvin, Turkey.
• 17 non-linear models were fitted using data from 406 trees for model development.
• Model performance was evaluated using R-squared (R2) and mean square error (MSE).
• Independent data from the remaining trees were used for model validation.

Main Results:

• Several models demonstrated similar height estimation capabilities.
• Model [8] achieved the highest R2 (0.8703) and the lowest MSE (5.47) during development.
• Model [8] and Model [16] showed the best height prediction accuracy on the independent validation dataset.

Conclusions:

• Model [8] is recommended for accurate height estimation of Picea orientalis L. in similar forest conditions.
• The study highlights the importance of model validation using independent data for reliable height predictions.
• Diameter and stand variables are effective predictors for Oriental spruce height estimation.