An approximate point-based alternative for the estimation of variance under big BAF sampling

Abstract Background A new variance estimator is derived and tested for big BAF (Basal Area Factor) sampling which a forest inventory system that utilizes Bitterlich (point sampling) with two sizes, small tree counts larger on measurements are made usually including DBHs heights needed volume estimation. Methods The using the Delta method from an existing formulation of as consisting three sample means. formula compared to estimators popular based Bruce’s formula. Results Several computer simulation studies were conducted comparing all known currently in literature. In simulations performed well comparably formulas. Conclusions possible advantage it does not require assumption negligible correlation between basal area factor volume-basal ratios large selection trees, required by previous estimation Although this was stands used study, conceivable could be significant some types, such those DBH-height relationship can affected substantially density perhaps through competition. We estimate covariance estimates mean ratio area. also mathematically expressions bias show approaches zero samples order $\frac {1}{n}$ 1 n where n number points.