Abstract
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.
Highlights
1.1 BackgroundStudies that accurately records the shape information of garden trees are insufficient even considering previous case studies of garden trees
In view of the above, this study proposes a method for constructing a 3D tree model with highly-accurate tree shape reproducibility from tree point cloud data using the terrestrial laser scanner (TLS)-QSM method
When restoring the planting, there were few materials that recorded tree shapes of Japanese gardens in their early days in detail, so the planting form were based on old photographs and ezu
Summary
Studies that accurately records the shape information of garden trees are insufficient even considering previous case studies of garden trees. There have been many studies that attempted to restore past garden plantings, but these are based on drawings, photographs, literature surveys, and drawing descriptions using picture scrolls, and there is no material that records the tree shape of that era in detail. Recording tree shape information using flat plate surveying is very limited. The reason is that trees have a complicated geometrical shape (Jucker, 2017)(Zhang, 2014)(Livny, 2010), which presents significant obstacles in data analysis. We focused on reconstructing tree shape characteristics, and considered the importance of 3D tree models of garden trees in Japanese gardens. In view of the above, this study proposes a method for constructing a 3D tree model with highly-accurate tree shape reproducibility from tree point cloud data using the TLS-QSM method
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