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Effects of Low-Carbon Visualizations in Landscape Design Based on Virtual Eye-Movement Behavior Preference

Author

Listed:
  • Zhengsong Lin

    (Virtual Landscape Design Laboratory, School of Art and Design, Wuhan Institute of Technology, Wuhan 430205, China)

  • Yuting Wang

    (Virtual Landscape Design Laboratory, School of Art and Design, Wuhan Institute of Technology, Wuhan 430205, China)

  • Xinyue Ye

    (Urban Data Science Laboratory, Department of Landscape Architecture and Urban Planning, Texas A&M University, College Station, TX 77840, USA)

  • Yuxi Wan

    (School of Art, Hubei University, Wuhan 430062, China)

  • Tianjun Lu

    (Department of Earth Science and Geography, California State University, Dominguez Hills, Carson, CA 90747, USA)

  • Yu Han

    (Urban Data Science Laboratory, Department of Landscape Architecture and Urban Planning, Texas A&M University, College Station, TX 77840, USA)

Abstract

Three-dimensional geovisualization in landscape design can be used to evaluate the efforts of mitigating CO 2 emissions. This study evaluated subjects’ emotional preferences for 3D landscape design through an eye movement tracking experiment. In the case that the color of the building materials was positively correlated with low carbon emissions, green, blue, and gray were typical representatives of low carbon emissions. Through the eye movement tracking experiment, subjects’ emotional preferences for different building colors were obtained. The results show that the fixation trajectory is consistent with the preset green and energy saving parameters, and the design effect of the architectural landscape can be evaluated by detecting virtual eye movement tracking. There is a coupling relationship between virtual eye movement tracking, expert interviews, and evaluation results, so that it presents a logical relationship between virtual eye movement, the color of low-carbon materials, and carbon emissions. In addition, the affective preference analysis and entropy weight method confirmed their effectiveness in the evaluation of the 3D landscape design effect, which had a positive impact on the CO 2 emission reduction of the construction industry. These results will contribute to the development of 3D landscape design in the architecture industry and provide new ideas and methods for the carbon peak project.

Suggested Citation

  • Zhengsong Lin & Yuting Wang & Xinyue Ye & Yuxi Wan & Tianjun Lu & Yu Han, 2022. "Effects of Low-Carbon Visualizations in Landscape Design Based on Virtual Eye-Movement Behavior Preference," Land, MDPI, vol. 11(6), pages 1-17, May.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:6:p:782-:d:824064
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    References listed on IDEAS

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    1. L. Margolin, 2005. "On the Convergence of the Cross-Entropy Method," Annals of Operations Research, Springer, vol. 134(1), pages 201-214, February.
    2. Binyi Liu & Zefeng Lian & Robert D. Brown, 2019. "Effect of Landscape Microclimates on Thermal Comfort and Physiological Wellbeing," Sustainability, MDPI, vol. 11(19), pages 1-13, September.
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    Cited by:

    1. Yu Cao & Cong Xu & Syahrul Nizam Kamaruzzaman & Nur Mardhiyah Aziz, 2022. "A Systematic Review of Green Building Development in China: Advantages, Challenges and Future Directions," Sustainability, MDPI, vol. 14(19), pages 1-29, September.
    2. Xinyi Chen & Yuyang Wang & Tao Huang & Zhengsong Lin, 2022. "Research on Digital Experience and Satisfaction Preference of Plant Community Design in Urban Green Space," Land, MDPI, vol. 11(9), pages 1-17, August.
    3. Xinhui Fei & Yanqin Zhang & Deyi Kong & Qitang Huang & Minhua Wang & Jianwen Dong, 2023. "Quantitative Model Study of the Psychological Recovery Benefit of Landscape Environment Based on Eye Movement Tracking Technology," Sustainability, MDPI, vol. 15(14), pages 1-19, July.

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