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A Survey of the Landscape Visibility Analysis Tools and Technical Improvements

International journal of environmental research and public health, 2023-01, Vol.20 (3), p.1788 [Peer Reviewed Journal]

2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2023 by the authors. 2023 ;ISSN: 1660-4601 ;ISSN: 1661-7827 ;EISSN: 1660-4601 ;DOI: 10.3390/ijerph20031788 ;PMID: 36767160

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  • Title:
    A Survey of the Landscape Visibility Analysis Tools and Technical Improvements
  • Author: Wu, Zhiqiang ; Wang, Yuankai ; Gan, Wei ; Zou, Yixuan ; Dong, Wen ; Zhou, Shiqi ; Wang, Mo
  • Subjects: Adaptation, Physiological ; Analytical methods ; Built Environment ; Cities ; City Planning - methods ; Complexity ; Computer applications ; Design ; Designers ; Humans ; Machine learning ; Methods ; Open spaces ; Optimization ; Regional development ; Resilience ; Spatial discrimination ; Urban areas ; Urban environments ; Urban planning ; Visibility ; Visual Perception ; Workflow
  • Is Part Of: International journal of environmental research and public health, 2023-01, Vol.20 (3), p.1788
  • Description: 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.
  • Publisher: Switzerland: MDPI AG
  • Language: English
  • Identifier: ISSN: 1660-4601
    ISSN: 1661-7827
    EISSN: 1660-4601
    DOI: 10.3390/ijerph20031788
    PMID: 36767160
  • Source: Open Access: PubMed Central
    Geneva Foundation Free Medical Journals at publisher websites
    AUTh Library subscriptions: ProQuest Central
    MEDLINE
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