Historic gardens, regarded as a significant genre of cultural heritage, encapsulate the enduring essence of bygone eras while concurrently transcending temporal boundaries to resonate with the present and future. These gardens provide us vitality and inspiration, holding a collective repository of human memory and serving as a testament to our shared heritage. However, like landscapes, gardens constantly change through natural processes and human interventions. How can we preserve these gardens, though changes are unavoidable? Spatial and visual characteristics are the gardens' essential characteristics, and point-cloud (LiDAR) technologies are powerful tools to reveal and analyze gardens’ spatial-visual relationships and characteristics. Therefore, this paper aims to present a point-cloud-based approach to identifying spatial-visual design principles and making them operational to protect and develop historic gardens. Additionally, several methods have been proposed in this research, including (a) a voxel-based method to transfer points into a solid model for GIS-based computation, (b) a novel method to analyze the field of view (FOV), and (c) a systemic framework to reveal historic gardens’ spatial-visual characteristics based on the voxelized model. Jichang Garden, a historic garden in Wuxi, China, known for its visual design and spatial arrangement, has been selected as a case study to showcase how to apply the methods proposed by this paper. The findings include the design principles for the water body, the arrangement for a route, and the planting strategies of the garden. The conservational strategies have been formed based on the findings, and the appliable potentials and limitations of the methods have also been discussed.@en

[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. […]@en

This paper focuses on GIS-based visibility analysis to explore landscape architecture com-positions as a means to understand visual-spatial characteristics and identify related design principles. More specifically, the paper elaborates a practical method to employ high-resolution data acquired by terrestrial LiDAR (Light Detection and Ranging or Laser Imaging Detection and Ranging) for this pur-pose. Though LiDAR provides a powerful means to digitally capture the real-world, methods like GIS-based visual landscape research that utilize viewshed analysis ideally require a continuous Digital Landscape Model conduct visibility computation. Therefore, one of the obstacles before the visual analysis is to process the points into surface or solid models. Voxel-based algorithms are powerful means to process LiDAR data. There are many applications known of voxel-based visibility analysis but requires often specialist software that is hard to handle or unavailable to landscape architects in practice. This paper showcases an attempt to use standard software for voxel-based visibility analysis. It presents a practical method for applications in landscape architecture analysis. Jichang Garden (Wuxi, China) is used as an example. The historical garden is an evocative example of a landscape architecture compo-sition that displays skilful applications of spatial-visual design principles and therefore worthy of ana-lyse. @en

Visual perception is crucial in landscape experience. Therefore, visual landscape research is an important field of inquiry that needs further development and applications (NIJHUIS 2011), and visibility analysis is the basis for further research. There are many methods and applications of landscape visibility analysis that have been developed and applied in the past decades. The pioneering work of Llobera explores the concept of “visual exposure”. He defined the visual exposure (V-E) as a measure of the visible portion of whatever is the focus of the investigation, which is about the surface area covered on the retina (LLOBERA 2003). In this research, a newly developed V-E computation algorithm for complex environments has been developed, which enables the analysis of views from multiple viewpoints. The West-Lake, a UNESCO world heritage site in Hangzhou (China), is used as a case study to compute the V-Es’ value for viewpoints on routes beside and around the lake. Finally, the method’s accuracy and the algorithm’s adoption potential have been evaluated.
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