Investigation of the Allometric Models in Estimation of Poplar (Populus deltoides) Height

One of the most important issues in forest biometrics is the use of allometric functions to estimate tree height by using diameter-height models. Measuring the total height of trees is usually a complex and time-consuming process. In allometric functions, the diameter is measured directly but the height of the tree is an estimate of an allometric model, which will be more accurate if the created models were correctly designed. For this reason, diameter-height models have been considered as an important element in forest management and monitoring nowadays. Therefore, we evaluated the performance of allometric models in estimating the height of this species in the present study. For this purpose, 32 allometric models were used and the coefficient of determination, standard error, Akaike coefficient, Root Mean Square Error, percentage of Root Mean Square Error, Bias, and percent of Bias criteria were used for estimating the accuracy of each model. The results showed that five models consisting of Loetsch, Ratkowsky, Hyperbolic 2, Hyperbolic 3, and Modified Geometry were able to measure the height of poplar trees (as the dependent variable) in terms of diameter of breast height (as the independent variable) with the highest amount of coefficient of determination (0.829-0.830), The lowest amounts of standard error (1.756-1.758), RMSE (0.682- 0.747 m), the RMSE% (3.177-3.511), Bias (-0.076 to -0.331), and Bias% (0.352 -1.558). In addition, the results of the t-test showed that there was no significant difference between the predicted values of height and the actual measured values of height. Consequently, these models were able to estimate the height of poplar trees without significant difference.