Continuous Measurement of Spatial Exposure Based on Visual Perception in Three-Dimensional Space
Authors: Nanjiang Chen
Abstract:
In the backdrop of expanding urban landscapes, accurately assessing spatial openness is critical. Traditional visibility analysis methods grapple with discretization errors and inefficiencies, creating a gap in truly capturing the human experience of space. Addressing these gaps, this paper presents a continuous visibility algorithm, providing a potentially valuable approach to measuring urban spaces from a human - centric perspective. This study presents a methodological breakthrough by applying this algorithm to urban visibility analysis. Unlike conventional approaches, this technique allows for a continuous range of visibility assessment, closely mirroring human visual perception. By eliminating the need for predefined subdivisions in ray casting, it offers a more accurate and efficient tool for urban planners and architects. The proposed algorithm not only reduces computational errors but also demonstrates faster processing capabilities, validated through a case study in Beijing's urban setting. Its key distinction lies in its potential to benefit a broad spectrum of stakeholders, ranging from urban developers to public policymakers, aiding in the creation of urban spaces that prioritize visual openness and quality of life. This advancement in urban analysis methods could lead to more inclusive, comfortable, and well-integrated urban environments, enhancing the spatial experience for communities worldwide.
Keywords: Visual openness, spatial continuity, ray-tracing algorithms, urban computation.
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[1] A. Tara and D. G. Lawson, ‘Calculating visual openness and visibility to natural landscapes in a changing urban landscape in Gold Coast, Australia’.
[2] S. Saeidi, S. H. Mirkarimi, M. Mohammadzadeh, A. Salmanmahiny, and C. Arrowsmith, ‘Assessing the visual impacts of new urban features: coupling visibility analysis with 3D city modelling’, Geocarto Int., vol. 34, no. 12, pp. 1315–1331, Oct. 2019, doi: 10.1080/10106049.2018.1478891.
[3] J. Krukar, C. Manivannan, M. Bhatt, and C. Schultz, ‘Embodied 3D isovists: A method to model the visual perception of space’, Environ. Plan. B Urban Anal. City Sci., vol. 48, no. 8, pp. 2307–2325, Oct. 2021, doi: 10.1177/2399808320974533.
[4] G. Kim, A. Kim, and Y. Kim, ‘A new 3D space syntax metric based on 3D isovist capture in urban space using remote sensing technology’, Comput. Environ. Urban Syst., vol. 74, pp. 74–87, Mar. 2019, doi: 10.1016/j.compenvurbsys.2018.11.009.
[5] M. L. Benedikt, ‘To Take Hold of Space: Isovists and Isovist Fields’, Environ. Plan. B Plan. Des., vol. 6, no. 1, pp. 47–65, Mar. 1979, doi: 10.1068/b060047.
[6] J. M. Wiener and G. Franz, ‘Isovists as a Means to Predict Spatial Experience and Behavior’, in Spatial Cognition IV. Reasoning, Action, Interaction, C. Freksa, M. Knauff, B. Krieg-Brückner, B. Nebel, and T. Barkowsky, Eds., in Lecture Notes in Computer Science. Berlin, Heidelberg: Springer, 2005, pp. 42–57. doi: 10.1007/978-3-540-32255-9_3.
[7] A. Turner, M. Doxa, D. O’Sullivan, and A. Penn, ‘From Isovists to Visibility Graphs: A Methodology for the Analysis of Architectural Space’, Environ. Plan. B Plan. Des., vol. 28, no. 1, pp. 103–121, Feb. 2001, doi: 10.1068/b2684.
[8] E. Morello and C. Ratti, ‘A digital image of the city: 3D isovists in Lynch’s urban analysis’, Authordept Web Page, Apr. 2009, Accessed: Mar. 07, 2024. Online. Available: https://dspace.mit.edu/handle/1721.1/55992
[9] J. Peponis, S. Bafna, and Z. Zhang, ‘The connectivity of streets: reach and directional distance’, Environ. Plan. B Plan. Des., vol. 35, no. 5, pp. 881–901, 2008, doi: 10.1068/b33088.
[10] A. E. Stamps, ‘Enclosure and Safety in Urbanscapes’, Environ. Behav., vol. 37, no. 1, pp. 102–133, Jan. 2005, doi: 10.1177/0013916504266806.
[11] Y. Lu, Y. Yang, G. Sun, and Z. Gou, ‘Associations between overhead-view and eye-level urban greenness and cycling behaviors’, Cities, vol. 88, pp. 10–18, May 2019, doi: 10.1016/j.cities.2019.01.003.
[12] K. A. Hart and J. J. Rimoli, ‘Generation of statistically representative microstructures with direct grain geometry control’, Comput. Methods Appl. Mech. Eng., vol. 370, p. 113242, Oct. 2020, doi: 10.1016/j.cma.2020.113242.
[13] Z. Zare, M. Yeganeh, and N. Dehghan, ‘Environmental and social sustainability automated evaluation of plazas based on 3D visibility measurements’, Energy Rep., vol. 8, pp. 6280–6300, Nov. 2022, doi: 10.1016/j.egyr.2022.04.064.
[14] OpenStreetMap Contributor, ‘Open Street Map’, Planet dump retrieved from https://planet.osm.org. Accessed: Jan. 06, 2023. Online. Available: https://www.openstreetmap.org/
[15] GaoDe, ‘Gaode Map Open Platform’. Accessed: Mar. 07, 2024. Online. Available: https://lbs.amap.com/