Determining the spatial distribution of tree heights at the regional area scale is significant when performing forest above-ground biomass estimates in forest resource management research. The geometric-optical mutual shadowing (GOMS) model can be used to invert the forest canopy structural parameters at the regional scale. However, this method can obtain only the ratios among the horizontal canopy diameter (CD), tree height, clear height, and vertical CD. In this paper, we used a semi-variance model to calculate the CD using high spatial resolution images and expanded this method to the regional scale. We then combined the CD results with the forest canopy structural parameter inversion results from the GOMS model to calculate tree heights at the regional scale. The semi-variance model can be used to calculate the CD at the regional scale that closely matches (mainly with in a range from − 1 to 1 m) the CD derived from the canopy height model (CHM) data. The difference between tree heights calculated by the GOMS model and the tree heights derived from the CHM data was small, with a root mean square error (RMSE) of 1.96 for a 500-m area with high fractional vegetation cover (FVC) (i.e., forest area coverage index values greater than 0.8). Both the inaccuracy of the tree height derived from the CHM data and the unmatched spatial resolution of different datasets will influence the accuracy of the inverted tree height. And the error caused by the unmatched spatial resolution is small in dense forest. The semi-variance model can be used to calculate the CD at the regional scale, together with the canopy structure parameters inverted by the GOMS model, the mean tree height at the regional scale can be obtained. Our study provides a new approach for calculating tree height and provides further directions for the application of the GOMS model.

中文翻译：

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在区域尺度上计算树高的新方法

在森林资源管理研究中进行森林地上生物量估计时，确定区域范围内树高的空间分布非常重要。几何光学互影（GOMS）模型可用于在区域尺度上反转森林冠层结构参数。但是，此方法只能获得水平树冠直径（CD），树高，净空高度和垂直CD之间的比率。在本文中，我们使用半方差模型使用高空间分辨率图像来计算CD，并将此方法扩展到区域范围。然后，我们将CD结果与GOMS模型的林冠结构参数反演结果结合起来，以计算区域尺度上的树高。半方差模型可用于计算与冠层高度模型（CHM）数据得出的CD紧密匹配（主要在-1 m至1 m范围内）的区域尺度上的CD。由GOMS模型计算得出的树高与从CHM数据得出的树高之间的差异很小，对于500 m高植被覆盖率（FVC）的区域，其均方根误差（RMSE）为1.96（即，森林面积覆盖指数值大于0.8）。从CHM数据得出的树高的不准确度以及不同数据集的无与伦比的空间分辨率都将影响倒立树高的精度。在茂密的森林中，由空间分辨率不匹配引起的误差很小。半方差模型可用于计算区域范围内的CD，结合GOMS模型反演的冠层结构参数，可以得到区域尺度上的平均树高。我们的研究提供了一种计算树高的新方法，并为GOMS模型的应用提供了进一步的指导。