Abstract
The Bitterlich Sampling (horizontal point sampling) is a common method in forest inventories. By this method, the Horvitz-Thompson estimator is used in a number of independent sampling points for the estimation of overall tree volume in a forest area/stand. In this paper, confidence intervals are constructed and evaluated using the normal approach and two bootstrap methods; the percentile method (Cα) and the bias-corrected and accelerated method (BCα). The simulation results show that the normal confidence interval has better coverage of true value at sample size 10. At sample sizes 20 and 30, it seems that there are no substantial differences in coverage between confidence intervals, although it could be noted a small superiority of BCα method. At sample size 40, the coverage of the three confidence intervals is higher than the nominal coverage (95%).
Highlights
Sampling in forest inventories is usually done by installing random points on the ground and selecting a group of trees around the points
The simulation results show that the normal confidence interval has better coverage of true value at sample size 10
At sample sizes 20 and 30, it seems that there are no substantial differences in coverage between confidence intervals, it could be noted a small superiority of BCα method
Summary
Sampling in forest inventories is usually done by installing random points on the ground and selecting a group of trees around the points. Trees are generally selected using the two most well-known forest sampling methods: the fixed-area plot sampling and Bitterlich Sampling (BS) or horizontal point sampling. In BS, the tree j is selected in the sample if the random point i is at a distance crj from the tree, where rj is the radius of the circular surface (cross-section) of the tree at 1.30 m height. Georgakis from the ground basal area and c is a constant, which is suitably selected to achieve a desired sampling density (Gregoire & Valentine, 2007; Roesch, Green, & Scott, 1993). The probability of selecting trees, by this method, is proportional to their basal area. The Horvitz-Thompson estimator can be used for parameter estimations such as the total volume of the forest area (Horvitz & Thompson, 1952; Schreuder, Gregoire, & Wood, 1993)
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