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首页> 外文期刊>African Journal of Agricultural Research >Analytical approaches for modeling tree crown volume in black wattle (Acacia mearnsii De Wild.) stands
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Analytical approaches for modeling tree crown volume in black wattle (Acacia mearnsii De Wild.) stands

机译:用于模拟黑荆树(Acacia mearnsii De Wild。)林木树冠体积的分析方法

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In this paper, four strategies were proposed for modeling tree crown volume using as independent variable stem variables, crown variables, combination of stem and crown variables, and stem volume. We used a dataset comprised of 170 trees from 12 temporary plots located in forest stands in southern Brazil. Models composed of stem variables presented weaker predictive ability. The best model contained crown variables, which explained 78.95% of observed variability. However, implementation of such model is bounded by its independent variables, which are not often measured in forest inventories. The model composed by diameter at breast height and crown length proved to be an adequate modeling approach. The predictive capability was kept by model which is composed by most easily measured variable in a forest - diameter at breast height, also by the most easily acquirable crown variable - crown length. In our suggested model, estimates of ?and ?are coefficients that convert volume of a regular geometric solid – RGS is dbh2 times crown length) - into crown volume, whilst estimate of ?is an allometric constant.
机译:在本文中,提出了四种树冠体积建模方法,分别使用自变量,茎变量,树冠变量,树冠和树冠变量的组合以及茎体积来建模。我们使用了一个数据集,该数据集由位于巴西南部森林林地的12个临时样地中的170棵树木组成。由茎变量组成的模型的预测能力较弱。最好的模型包含冠变量,解释了观察到的变异的78.95%。但是,这种模型的实施受到其独立变量的限制,这些变量通常在森林资源清查中无法衡量。由乳房高度和冠长的直径组成的模型被证明是适当的建模方法。预测能力由模型保持,该模型由森林中最容易测量的变量-胸高的直径,也由最容易获得的树冠变量-树冠长度组成。在我们建议的模型中,对?和?的估计是将规则几何实体的体积(RGS是dbh2乘以冠的长度)转换为冠的体积,而对?的估计则是一个测距常数。

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