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Maximum likelihood parametric reconstruction of forest vertical structure from inclined laser quadrat sampling

机译:基于倾斜激光四边采样的森林垂直结构最大似然参数重构。

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Forest vertical structure is critical to ecological function, and provides a crucial link to air- and spaceborne remote sensing (including LiDAR), but is difficult to measure from the ground. Laser point quadrat sampling has been suggested as one alternative, but previous statistical approaches to modeling forest structure using such data have required impractical sample sizes. Here, I develop the theory for maximum likelihood estimation of a parametric model of forest vertical structure, and illustrate it using inclined point quadrat sampling with a handheld laser. Results from three forest stands in arctic Norway suggest excellent qualitative agreement with structure derived from alternative methods. The approach generalizes readily to other hardware configurations, including terrestrial laser scanning.
机译:森林的垂直结构对于生态功能至关重要,并提供了与空天遥感(包括LiDAR)的关键链接,但很难从地面进行测量。已经提出了激光点积取样作为一种替代方法,但是使用这种数据对森林结构进行建模的先前统计方法需要不切实际的样本量。在这里,我开发了用于森林垂直结构参数模型的最大似然估计的理论,并说明了通过手持式激光器使用倾斜点四边形采样的方法。挪威北极地区三个森林林分的结果表明,从替代方法得出的结构具有极好的定性一致性。该方法很容易推广到其他硬件配置,包括地面激光扫描。

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