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Seeing the trees despite the forest - Methods for counting trees based on distance measurements

机译:在森林中看树木-基于距离测量的树木计数方法

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摘要

Multi-purpose forest inventories are focused on a broad set of target variables. However, many of these target variables are derived from estimates of a single important attribute, namely the number of trees per area unit. Obtaining an accurate estimate of the tree density can therefore be considered as a crucial prerequisite in various forest inventory settings. Counting the number of trees in a forest seems to be trivial at first glance, but it can be challenging in fact (i) if an improper samplingapproach is used, (ii) when trees are sparse, and (iii) if trees are masked by obstacles or limited sighting conditions. We will show different approaches (i) to correct the design-based biased /c-tree sampling estimator, (ii) to efficiently sample raretrees, and (iii) to correct for the bias introduced by missing trees due to limited sighting conditions. The paper demonstrates statistical methodology how to answer the central question: "How many trees are in the forest?"
机译:多功能森林清单着重于广泛的目标变量。但是,许多这些目标变量是从单个重要属性(即每单位面积的树木数量)的估计得出的。因此,在各种森林资源清查设置中,获得树木密度的准确估计值是至关重要的前提。乍看之下,对森林中树木的数量进行计数似乎微不足道,但实际上(i)如果使用了不正确的采样方法,(ii)树木稀疏时,(iii)如果树木被遮盖住,这可能是一个挑战。障碍物或瞄准条件有限。我们将展示不同的方法(i)纠正基于设计的有偏差的/ c-tree采样估计器,(ii)有效地对稀有树进行采样,以及(iii)纠正由于瞄准条件有限而缺少树木造成的偏差。本文展示了统计方法论如何回答核心问题:“森林中有几棵树?”

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