Authors: RAMAZAN ÖZÇELİK, TUNCAY ERASLAN
Abstract: The accurate estimation of tree biomass is crucial for the efficient management of forest resources. In this study, we used a subsampling method for unbiased estimates of above-ground tree biomass. The method consists of 2 stages: the first stage consists of randomized branch sampling (RBS) and the second stage uses importance sampling (IS). RBS is used to select a path from the butt of an object branch to a terminal segment. IS is used for selecting a disk that produces unbiased estimates of the fresh biomass of tree. In this study, the subsampling method was tested on 14 black pine sample trees (Pinus nigra Arnold subsp. pallasiana (Lamb.) Holmboe) in order to estimate the trees' biomass quickly and easily. The results showed a wide range of sampling error per tree, ranging from 2.51% to 22.63%. However, the sampling error for the total biomass of the 14 trees tested was only 2.65%. The proposed 2-stage sampling method generally performed better for the bole biomass than the branch biomass. These results indicated that the proposed 2-stage sampling method is effective and might overcome many of the identified constraints in biomass estimation. It is a viable alternative to the current methods used in Turkey.
Keywords: Biomass, black pine, importance sampling, randomized branch sampling, subsampling
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