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The Estimation of Tree Height Based on LiDAR Data and QuickBird Imagery

机译:基于LiDAR数据和QuickBird影像的树木高度估计。

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The estimation of tree height is advanced following the development of LiDAR technique. The estimation model of tree height considering suppressed trees is developed in order to extract tree height accurately using LiDAR data. Filtered LiDAR data and Quickbird imagery are segmented using watershed segmentation method based on mathematical morphology to get the boundary of trees. And the highest point in each canopy object is used to estimate tree height. Weibull distribution is used to estimate height distribution of the suppressed trees. The experiment results indicate that the watershed segmentation method based on mathematical morphology is an effective method to extract the boundary of trees. And the R~2 between the tree height estimated using estimation model of tree height considering suppressed trees and the tree height measured by field work is 0.93.
机译:随着LiDAR技术的发展,对树高的估计得到了提高。建立了考虑被抑制树木的树木高度估计模型,以便使用LiDAR数据准确提取树木高度。利用基于数学形态学的分水岭分割方法对滤波后的LiDAR数据和Quickbird图像进行分割,得到树木的边界。每个树冠对象中的最高点用于估计树的高度。威布尔分布用于估计抑制树的高度分布。实验结果表明,基于数学形态学的分水岭分割方法是提取树木边界的有效方法。使用考虑抑制树木的树木高度估计模型估计的树木高度与通过野外工作测得的树木高度之间的R〜2为0.93。

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