Combination of high order kernel estimators for estimation of fruit trees biomass on critical land

Abstract

This study aims to estimate fruit tree biomass with a high-order Gaussian kernel estimator. The source of the data was obtained by estimating the relationship between tree diameter (x) and tree biomass (y) which was obtained through the allometric equation y = 0.11ρx2.62 for branched trees. Data samples were taken as many as 250 obtained from 5 sub-district locations in critical land on longan and mango fruit tree vegetation. The relationship between x and y is then estimated in the form of an equation yi = m (xi) + εi where, i = 1, 2, n. The results of the analysis using the kernel estimator showed that the tree biomass estimation resulted in a smooth regression curve at an optimal bandwidth (h) score of 1.3 (GCV = 122.92) longan and 2.6 (GCV = 3523.25) mango. The relationship between MSE and bandwidth shows a very strong negative correlation with a score of r = -0.959 (p.value = 0.04) in the estimated longan biomass and r = -0.964 (p.value = 0.03) in the estimated mango biomass and is significant (α = 0.05). This means that a parallel increase in the bandwidth score will decrease the MSE score when GCV is controlled.