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Using mathematical morphology on LiDAR data to extract information from urban vegetation

机译:在LiDAR数据上使用数学形态学从城市植被中提取信息

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Accurate delineation of individual tree crowns in human settlement is of vital importance to decision-making in environmental management. Increasing availability of LiDAR data and applications of mathematical morphology imply a paradigm shift in tree crown delineation. This paper introduces a new approach based on “mathematical morphology on grey-level images” that enables such delineation. We consider a LiDAR data set as a grey-level image in which the indexes are the (x,y) locations on the grid and in which each value is the corresponding height of the point acquired by using the LiDAR sensor (i.e. top of the tree at the (x,y) location). We have applied this approach to a large data set in the frame of a partnership with a Hungarian University, and the results we obtain are closely related to what can be seen on a 3D visualization of the LiDAR data set.
机译:在人类住区中准确描绘单个树冠对环境管理决策至关重要。 LiDAR数据可用性的提高和数学形态学的应用意味着树冠轮廓的范式转移。本文介绍了一种基于“灰度图像上的数学形态学”的新方法,可以进行这种描述。我们将LiDAR数据集视为灰度图像,其中索引是网格上的(x,y)位置,并且每个值是使用LiDAR传感器获取的点的相应高度(即(x,y)位置的树)。在与匈牙利大学建立合作伙伴关系的框架内,我们已将此方法应用于大型数据集,并且我们获得的结果与在LiDAR数据集的3D可视化中可以看到的内容密切相关。

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