Additivity of tree biomass components using ratio estimate

Abstract

This study deals with the subject biomass estimation. The objective was to achieve the additivity of tree biomass components, which is defined as the compatibility among the component predictions and total tree biomass, using ratio estimates. The biomass estimation model was applied to black wattle trees in forest stands, which include a sample of 670 trees in an age range of 1 to 10.75 years. The adjusted model, in which the total biomass, or sum of predicted components, is a function of the stem volume multiplied by the Scalar Coefficients Proxy of Density, proved to be of great interest for biomass estimation and consistent when compared to the results obtained by WNSUR estimates (traditional method). The natural additivity of the tree biomass components was fully achieved, when modeling them by means of ratio estimation. Equations developed from the proportional behavior of the biomass components at different ages did not require the use of linear regression models and were obtained from calibration with the experimental data. The estimators resulting from these equations proved to be appropriate to make a generic model for correction of ratios coefficients at different ages.

Predicting Stand Volume by Number of Trees Automatically Detected in UAV Images: An Alternative Method for Forest Inventory

“…By using these pre-existing data, field sampling was not required for volume estimation modeling, allowing a practical and quick estimation method. Based on [36,38], we estimated the variance (Equation ( 3)), standard error (Equation ( 4)), confidence interval (Equation ( 5)), and relative error (Equation ( 6)) of the form factor, represented by the ratio estimator ( Rj ).…”

“…We estimated the variance, standard error, confidence interval, and relative error for the mean individual volume ( ŷ) obtained from the scaling dataset (Equations ( 11) to (14) and for the estimated total volume ( Ŷ) (Equations ( 15) to ( 18)) based on a previous study [38]. Where N is the number of trees in the stand, n is the number of scaled trees, t is Student's t-distribution, Rj = ratio estimator, x i = is the volume of the scaled log cylinders, y i = individual volume per scaled tree, and x = mean volume of scaled log cylinders.…”