Application of 3D tree modeling using point cloud data by terrestrial laser scanner
Application of 3D tree modeling using point cloud data by terrestrial laser scanner
复制标题
DOI：
10.5194/isprs-archives-xliii-b3-2020-995-2020
复制
发表时间：
2020-08
期刊：
影响因子：
--
通讯作者：
R. Kumazaki;Y. Kunii
中科院分区：
文献类型：
--
作者：
R. Kumazaki;Y. Kunii
抽象的。为树木建立3D模型，比如在日本花园中发现的树木，其中存在许多物种，需要生成结合树木物种特征和自然多样性的树木形状。因此，本研究提出了一种从TLS获取的树木点云数据中构建具有高精度树木形状重现性的三维树木模型的方法。作为一种方法，我们尝试使用TLS-QSM方法的开源TreeQSM来构建3D树模型。然而，在TreeQSM中，由于处理是基于树点云由与树干和树枝相关的数据组成的假设，因此推荐测量落叶的树木。为了解决这一问题，我们提出了一种有效的分类过程，该过程主要使用偏差阈值和反射率阈值，这些阈值是可以通过激光测量获得的物体的辅助数据。此外，为了验证模型的准确性，从构建的三维树木模型中提取位置坐标。将提取的坐标与树木点云数据的坐标进行比较，以明确从树木点云数据构建3D树模型的程度。结果，在与树木点云数据的标准偏差为0.016 m的范围内构建了3D树木模型。因此，TLS-QSM方法对树形的重现性在精度方面也是有效的。
Abstract. Constructing 3D models for trees such as those found in Japanese gardens, in which many species exist, requires the generation of tree shapes that combine the characteristics of the tree's species and natural diversity. Therefore, this study proposes a method for constructing a 3D tree model with highly-accurate tree shape reproducibility from tree point cloud data acquired by TLS. As a method, we attempted to construct a 3D tree model using the TreeQSM, which is open source for TLS-QSM method. However, in TreeQSM, since processing is based on the assumption that the tree point cloud consists of data related to trunks and branches, measuring trees in which leaves have fallen is recommended. To solve this problem, we proposed an efficient classification process that mainly uses thresholds for deviation and reflectance, which are the adjunct data of the object that can be acquired by laser measurement. Furthermore, to verify accuracy of the model, position coordinates from the constructed 3D tree model were extracted. The extracted coordinates were compared with the those of the tree point cloud data to clarify the extent to which the 3D tree model was constructed from the tree point cloud data. As a result, the 3D tree model was constructed within the standard deviation of 0.016 m from the tree point cloud data. Therefore, the reproducibility of the tree shape by the TLS-QSM method was also effective in terms of accuracy.