Fitting cubic interpolating polynomials to tree stem mensuration data

This paper discusses the nonlinear third interpolating polynomials on tree growth data based on volumetric equations used in Forestry Science. Data variables used are diameter of stem at breast height (Dbh), base (Db), middle (Dm) and top (Dt), just before the crown, with their corresponding stem height of tree or bole (ST). There are 130 mensuration data samples, and the cubic interpolating polynomials are interpolated using Maple. To obtain a robust model for biomass estimation, comparisons are simulated and the best model is selected, based on the sum of square error (SSE). Results obtained indicate the range of the constants and β-coefficients of the polynomials. The models are statistically significant based on the variance analysis. The best cubic interpolating model, however, is found to be an asymptotic curve with the parameters from mensuration data. This is with respect to the different tree volumetric equations for biomass estimation.