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基于点云技术的景观空间密度量化方法研究 被引量:1

Research on Quantification Method for Landscape Space Density Based on Point Cloud Technology
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摘要 点云技术的发展为景观空间的精确量化与精准设计提供了重要机遇。选取过往研究中多通过人工实地调研与经验估算的“景观空间密度”指标,利用点云等数字技术优化其量化方法。首先,以无人机倾斜摄影与地面激光雷达扫描生成的点云模型为基础,通过点云体元化得到景观要素的三维形态,进而计算出总体空间密度;其次,利用Grasshopper对空间密度的三维分布加以可视化;最后以东南大学梅庵周边景观空间为例,探讨该方法的实用性。由此发现,基于点云技术的景观空间密度量化方法在数据采集处理的效率、计算结果的精度以及结果的可读性等方面有显著优势,有利于更加直观、准确地为景观空间设计提供针对性的优化策略。 The development of point cloud technology provides an essential opportunity for the accurate quantification and precise design of landscape space.In this research,the landscape space density(LSD)index,typically estimated on the basis of field research and experience in previous researches,is selected to optimize the quantification method adopted by using point cloud and other digital technologies.Firstly,based on the point cloud model generated by unmanned aerial vehicle tilt photography and ground-based radar scanning,this research figures out the three-dimensional morphology and overall space density of landscape elements through point cloud voxelization.Then,it visualizes the three-dimensional distribution of space density by Grasshopper.Finally,it takes the landscape space around Meian building in Southeast University as an example to explore the practical application of the quantification method.Research results shows that the proposed method has outstanding advantages in such aspects as the efficiency of data collection and processing,accuracy of calculation and readability of results,and may thus help to provide targeted optimization strategies for landscape design in a more intuitive and accurate way.
作者 张潇涵 成玉宁 ZHANG Xiaohan;CHENG Yuning(the School of Architecture,Southeast University;the Department of Landscape Architecture,the School of Architecture,Southeast University)
出处 《风景园林》 2022年第6期84-89,共6页 Landscape Architecture
基金 国家自然科学基金(编号51838003) 国家自然科学基金青年科学基金(编号52108045) 国家重点研发计划(编号2019YFD1100405)。
关键词 风景园林 点云技术 既有空间 景观空间密度 空间形态 landscape architecture point cloud technology existing space landscape space density(LSD) spatial morphology
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