A Survey of the Landscape Visibility Analysis Tools and Technical Improvements

Zhiqiang Wu, Yuankai Wang (), Wei Gan (), Yixuan Zou, Wen Dong, Shiqi Zhou and Mo Wang
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Zhiqiang Wu: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Yuankai Wang: Bartlett School of Architecture, University College London, London WC1H0QB, UK
Wei Gan: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Yixuan Zou: Shanghai Tongji Urban Planning & Design Institute Co., Ltd., Shanghai 200092, China
Wen Dong: Shanghai Tongji Urban Planning & Design Institute Co., Ltd., Shanghai 200092, China
Shiqi Zhou: College of Design and Innovation, Tongji University, Shanghai 200093, China
Mo Wang: College of Architecture and Urban Planning, Guangzhou University, Guangzhou 510006, China

IJERPH, 2023, vol. 20, issue 3, 1-23

Abstract: Visual perception of the urban landscape in a city is complex and dynamic, and it is largely influenced by human vision and the dynamic spatial layout of the attractions. In return, landscape visibility not only affects how people interact with the environment but also promotes regional values and urban resilience. The development of visibility has evolved, and the digital landscape visibility analysis method allows urban researchers to redefine visible space and better quantify human perceptions and observations of the landscape space. In this paper, we first reviewed and compared the theoretical results and measurement tools for spatial visual perception and compared the value of the analytical methods and tools for landscape visualization in multiple dimensions on the principal of urban planning (e.g., complex environment, computational scalability, and interactive intervention between computation and built environment). We found that most of the research was examined in a static environment using simple viewpoints, which can hardly explain the actual complexity and dynamic superposition of the landscape perceptual effect in an urban environment. Thus, those methods cannot effectively solve actual urban planning issues. Aiming at this demand, we proposed a workflow optimization and developed a responsive cross-scale and multilandscape object 3D visibility analysis method, forming our analysis model for testing on the study case. By combining the multilandscape batch scanning method with a refined voxel model, it can be adapted for large-scale complex dynamic urban visual problems. As a result, we obtained accurate spatial visibility calculations that can be conducted across scales from the macro to micro, with large external mountain landscapes and small internal open spaces. Our verified approach not only has a good performance in the analysis of complex visibility problems (e.g., we defined the two most influential spatial variables to maintain good street-based landscape visibility) but also the high efficiency of spatial interventions (e.g., where the four recommended interventions were the most valuable), realizing the improvement of intelligent landscape evaluations and interventions for urban spatial quality and resilience.

Keywords: landscape; visible green; 3D Isovist; spatial configuration; built environment (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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