Improving the accuracy of the height–diameter equation using the classified factors method

Abstract

The height–diameter relationship model is crucial in the estimation of forest stand volume, biomass and carbon storage, etc. To improve prediction accuracy, the classified factors method for height–diameter relationship modeling was developed based on the classified height method. The data set contained 959 tree samples obtained from 28 plots measured by topographic factors (aspect, slope position and altitude). The Chapman–Richards equation was used to build models. Classification methods have improved fitting performance and prediction accuracy compared to the classical method. The classified height method has the best fitting performance because it has the highest determination coefficient (R 2 = 0.927) and the lowest root mean square error (RMSE = 1.548), whereas the classified factors method has the highest prediction accuracy because it has the lowest mean absolute error (MAE = 1.137) and mean relative error (MRE = 0.109).