CN 11-5366/S     ISSN 1673-1530
引用本文: 张冠亭,彭予洋,史蒂芬·奈豪斯.基于LiDAR点云的中国传统园林视觉空间定量分析方法:以寄畅园为例[J].风景园林,2024,31(7):108-114.
ZHANG G T, PENG Y Y, NIJHUIS S. Method for Quantitative Analysis of Visual Space of Chinese Traditional Gardens Based on LiDAR Point Cloud: A Case Study of Jichang Garden[J]. Landscape Architecture, 2024, 31(7): 108-114.
Citation: ZHANG G T, PENG Y Y, NIJHUIS S. Method for Quantitative Analysis of Visual Space of Chinese Traditional Gardens Based on LiDAR Point Cloud: A Case Study of Jichang Garden[J]. Landscape Architecture, 2024, 31(7): 108-114.


Method for Quantitative Analysis of Visual Space of Chinese Traditional Gardens Based on LiDAR Point Cloud: A Case Study of Jichang Garden

  • 摘要:
    目的 中国传统园林空间复杂多变,传统的分析方法难以深入探索传统园林复杂的三维视觉空间特征。三维激光雷达(light detection and ranging, LiDAR)点云技术在传统园林空间研究方面具有精度高、信息全等优势,借助LiDAR点云技术深入探索中国传统园林视觉空间特征,可为现代人居环境空间营造提供借鉴与参考。
    方法 基于LiDAR点云技术提出一套适用于中国传统园林视觉空间分析的方法,并以三维可视性、视野舒展度及景物视野占比3项指标量化描述视觉空间。
    结果 以寄畅园为例,构建了寄畅园LiDAR点云体素模型,利用提出的方法对锦汇漪西侧滨水步道11个视点的视觉空间进行了量化分析,解析了寄畅园的视觉空间特征,并探究了该步道的空间感知序列。
    结论 证实了利用LiDAR点云技术展开传统园林视觉空间研究的可行性与准确性,提出的方法可应用于其他传统园林视觉空间的分析研究中。


    Objective Human perception of landscape and environment is primarily through visual senses, making visual landscape research a central theme in landscape architecture research. Conducting a visual analysis of the spatial characteristics of traditional Chinese gardens and exploring their visual features can provide valuable guidance for inheriting the essence of spatial design. In recent years, many scholars have employed quantitative analytical methods to identify the visual space of traditional gardens. However, few of these studies have used detailed models to analyze the spatial features of traditional garden spaces. Compared to traditional digital models, point cloud models collected through LiDAR (light detection and ranging) offer more detailed spatial information for visual landscape research. Therefore, this research aims to take Jichang Garden in Wuxi as an example to explore the possibilities and applications of in-depth visual and spatial analysis of traditional Chinese gardens using point cloud technology. This aim can be further broken into several components: 1) Establishing analytical methods and selecting analysis indicators; 2) applying these methods and indicators to analyze the visual space of Jichang Garden; 3) uncovering the characteristics and features of traditional Chinese gardens through the interpretation of analysis results.
    Method This research establishes a set of methods for quantifying the analysis of visual space using point cloud data, including three main steps. 1) Establishment of a model based on point cloud for calculating the analysis results of visual space. In detail, this research applies a voxel-based method to build multidimensional digital models for buildings, vegetation, and rockery, and build a digital elevation model (DEM) based on the point cloud data on the ground. Then, the aforesaid two kinds of models are integrated with water surface to finalize the modeling process. 2) Establishment of a visual analysis method (line of sight method) based on the three-dimensional digital model for obtaining visual space information. 3) Proposal of indicators for evaluating visual landscape utilizing the visual space information obtained, including “3D visibility”, “visual spread” and “feature ratio of visual field” indicators. A total of 11 viewpoints (viewpoints 1, 2, 3 ... 11) on the west side of Jinhuiyi Pond are analyzed using the above methods.
    Results This research’s main findings consist of three parts. 1) 3D visibility calculation results. From the visibility analysis results of 11 viewpoints, it is evident that viewpoints 1, 5, 6, 7, and 10 have a relatively broad visual field, with some line of sight reaching a length of 100 meters. 2) Evaluation results of visual space indicators. The viewpoint with the highest 3D visibility is labeled as viewpoint 1, located at the Xianyuexie water viewing platform, while the one with the minimum 3D visibility is labeled as viewpoint 2. The viewpoint with the highest “visual spread” is viewpoint 10, situated in the plaza at the south of the Jiashutang building, while the one with the minimum “visual spread” is viewpoint 11. Except for viewpoint 1 (dominated by buildings) and viewpoint 10 (dominated by the ground), the highest “feature ratio of visual field” is occupied by vegetation. 3) Interpretation of the calculation results. Firstly, the research interprets the reasons for forming a scenic view from a single viewpoint. “3D visibility” can be used to identify the scale of the visual field in gardens. At the same time, the “feature ratio of visual field” can be employed to analyze the factors contributing to the scale of visual space. Moreover, incorporating the “visual spread” indicator further makes it possible to identify the morphological features of visual space in traditional gardens. Secondly, the research explores route-based visual space transitions. From the perspective of landscape sequence, visitors, starting from the Xianyuexie water viewing platform and passing through Hebutan (a small pond) to reach the Jiashutang building, undergo at least the following spatial perception processes. 1) Xianyuexie – woody path (near Jiushitai): Visitors transition from the lake viewing space beside the Xianyuexie building to the enclosed space surrounded by a group of trees along the path. 2) Woody path – Hebutan: Visitors experience a shift from a relatively enclosed environment to a more open water viewing space. The peak of this water viewing experience occurs near viewpoint 5 (Hebutan), a space with water on three sides. 3) Hebutan – waterside path (near Bayinjian): Visitors’ experience transitions from an open water viewing space to a more enclosed space where the view of the lake is obstructed by plants, enriching the water viewing experience and preventing aesthetic fatigue resulting from continuous exposure to similar spatial environments. 4) Waterside path– Jiashutang: Visitors’ experience evolves from a closed, plant-dominated space to a gradually more open lake viewing space in front of the Jiashutang building, serving as the endpoint of the entire perceptual space sequence on the west side of Jinhuiyi Pond.
    Conclusion In summary, the conclusions of this research are as follows: Firstly, point cloud technology has a specific feasibility for analyzing the spatial and visual characteristics of traditional Chinese gardens, and its high accuracy and precision make it suitable for handling the complex and varied spatial conditions of traditional Chinese gardens. Secondly, the three visual space indicators proposed in this research have a solid capability for explaining the characteristics of garden space.