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首页> 外文期刊>Journal of Sustainable Forestry >Total and merchantable volume equations for Tectona grandis Linn. f. plantations in Karnataka, India.
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Total and merchantable volume equations for Tectona grandis Linn. f. plantations in Karnataka, India.

机译:Tectona grandis Linn的总体积和可销售体积方程。 F。印度卡纳塔克邦的人工林。

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摘要

Tectona grandis (teak) is one of the most important timber species worldwide and India is one of the major teak growing countries. Though some volume equations were developed in the past in India, merchantable volume equations (any top diameter or bole length) are not available. Moreover, the models developed were neither quantitatively and qualitatively evaluated nor validated with independent data sets. Hence, the objective of this study was to develop appropriate volume equations to predict total tree volume and merchantable volume for teak in Karnataka. Linear and non-linear equations were used to model the relationship of the volume with respect to diameter at breast height (dbh) and total height. Merchantable volume equations for estimating merchantable volume to any minimum top diameter or bole length have also been constructed. The equations tested mostly fitted well to the data. Other models developed elsewhere tended to underestimate the volume, especially at dbh >=23 cm. The geometric cylinder volume equation, in combination with a stem form factor of .40, is widely used for teak in Karnataka but they were found to be less precise compared to regression equations when applied to the present data set. Model validation indicated that models should be calibrated with local data for greater accuracy in the prediction.
机译:Tectona grandis(柚木)是世界上最重要的木材品种之一,而印度则是柚木的主要生产国之一。尽管过去在印度开发了一些体积方程,但尚无可销售的体积方程(任何顶部直径或桶长)。此外,所开发的模型既未进行定量和定性评估,也未使用独立的数据集进行验证。因此,本研究的目的是开发适当的体积方程式,以预测卡纳塔克邦柚木的总树木体积和可销售量。使用线性和非线性方程来对体积与乳房高度(dbh)和总高度上的直径之间的关系进行建模。还构建了可商购的体积方程,用于将可商购的体积估算为任何最小的顶部直径或钻杆长度。测试的方程式非常适合数据。其他地方开发的其他模型往往会低估体积,尤其是在dbh> = 23 cm时。几何圆柱体体积方程式与0.40的杆形系数相结合,在卡纳塔克邦广泛用于柚木,但发现将其应用于当前数据集时,与回归方程式相比,它们的精度较差。模型验证表明,应使用本地数据对模型进行校准,以提高预测的准确性。

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