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Eye-tracking technology, visual preference surveys, and urban design: preliminary evidence of an effective methodology

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  • Robert B. Noland
  • Marc D. Weiner
  • Dong Gao
  • Michael P. Cook
  • Anton Nelessen

Abstract

Urban planners and designers use visual preference surveys to gather public opinion on potential designs for developments. Using eye-tracking technology, we administered a visual preference survey to a convenience sample to evaluate quantitatively the ways in which individuals process and rank images used in public settings for urban planning. We combined both a subjective qualitative analysis with quantitative evaluation of the eye-tracking data. The analysis largely confirms that various new urbanist components of the images, namely people, pedestrian features, and greenery, lead to higher rankings. Images with cars and parking receive negative rankings. Buildings, which are a key component of architectural design, had mixed results. The analysis demonstrates the efficacy of visual preference surveys. We show a way for transportation and urban planners to extract greater value from visual preference surveys, consistent with efforts to increase pedestrian activity while reducing motor vehicle traffic in cities.

Suggested Citation

  • Robert B. Noland & Marc D. Weiner & Dong Gao & Michael P. Cook & Anton Nelessen, 2017. "Eye-tracking technology, visual preference surveys, and urban design: preliminary evidence of an effective methodology," Journal of Urbanism: International Research on Placemaking and Urban Sustainability, Taylor & Francis Journals, vol. 10(1), pages 98-110, January.
    • Handle: RePEc:taf:rjouxx:v:10:y:2017:i:1:p:98-110
    DOI: 10.1080/17549175.2016.1187197
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    References listed on IDEAS

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    1. Michel Wedel & Rik Pieters, 2000. "Eye Fixations on Advertisements and Memory for Brands: A Model and Findings," Marketing Science, INFORMS, vol. 19(4), pages 297-312, October.
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    2. Anciaes, Paulo & Jones, Peter, 2020. "Transport policy for liveability – Valuing the impacts on movement, place, and society," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 157-173.
    3. Nawaf Saeed Al Mushayt & Francesca Dal Cin & Sérgio Barreiros Proença, 2021. "New Lens to Reveal the Street Interface. A Morphological-Visual Perception Methodological Contribution for Decoding the Public/Private Edge of Arterial Streets," Sustainability, MDPI, vol. 13(20), pages 1-21, October.
    4. James Simpson & Kevin Thwaites & Megan Freeth, 2019. "Understanding Visual Engagement with Urban Street Edges along Non-Pedestrianised and Pedestrianised Streets Using Mobile Eye-Tracking," Sustainability, MDPI, vol. 11(15), pages 1-17, August.
    5. Wenqing Ding & Qinqin Wei & Jing Jin & Juanjuan Nie & Fanfan Zhang & Xiaotian Zhou & Youhua Ma, 2023. "Research on Public Space Micro-Renewal Strategy of Historical and Cultural Blocks in Sanhe Ancient Town under Perception Quantification," Sustainability, MDPI, vol. 15(3), pages 1-17, February.
    6. Tingting Su & Kaiping Wang & Shuangshuang Li & Xinyan Wang & Huan Li & Huanru Ding & Yanfei Chen & Chenhui Liu & Min Liu & Yunlu Zhang, 2022. "Analysis and Optimization of Landscape Preference Characteristics of Rural Public Space Based on Eye-Tracking Technology: The Case of Huangshandian Village, China," Sustainability, MDPI, vol. 15(1), pages 1-25, December.
    7. Ruoshi Zhang & Weiyue Duan & Zhikai Zheng, 2024. "Multimodal Quantitative Research on the Emotional Attachment Characteristics between People and the Built Environment Based on the Immersive VR Eye-Tracking Experiment," Land, MDPI, vol. 13(1), pages 1-27, January.

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