IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i7p3799-d777873.html
   My bibliography  Save this article

The Perceived Restorative Quality of Viewing Various Types of Urban and Rural Scenes: Based on Psychological and Physiological Responses

Author

Listed:
  • Chang Li

    (School of Architecture and Urban Planning, Suzhou University of Science and Technology, Suzhou 215000, China)

  • Yu Yuan

    (School of Architecture and Urban Planning, Suzhou University of Science and Technology, Suzhou 215000, China)

  • Changan Sun

    (School of Education, Suzhou University of Science and Technology, Suzhou 215000, China)

  • Minkai Sun

    (School of Architecture and Urban Planning, Suzhou University of Science and Technology, Suzhou 215000, China)

Abstract

Attention restoration theory argues that the type of visual scene is important; however, related research is mostly based on a dichotomous comparison between natural and urban environments. Few studies have evaluated complex scenes comprising both natural and artificial elements. Therefore, we compared the differences between four types of environments: urban artificial scenes, urban natural scenes, rural artificial scenes, and rural natural scenes—using a survey based on the Perceived Restorativeness Scale (PRS), perception complexity scoring, and eye tracking. Participants ( N = 119) viewed photographs in a random order. The results showed significant differences between the visual landscape scores and eye-tracking data for each type of visual image: PRS, perception complexity, average fixation duration, and mean pupil size. Rural natural scenes had a higher restoration effect than the other scenes. Waterscapes and well-maintained vegetation had positive correlations between the typical landscape element indices and restorative benefits in different scene types. Contrastingly, weeds and hardscapes showed negative correlations, which can be attributed to the maintenance of these typical elements. The harmony of elements with circumstances in a scene was a key factor. The results provide a reference for urban and rural landscape planning and design to improve perceived restorative quality.

Suggested Citation

  • Chang Li & Yu Yuan & Changan Sun & Minkai Sun, 2022. "The Perceived Restorative Quality of Viewing Various Types of Urban and Rural Scenes: Based on Psychological and Physiological Responses," Sustainability, MDPI, vol. 14(7), pages 1-21, March.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:7:p:3799-:d:777873
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/7/3799/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/7/3799/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Youngeun Kang & Eujin Julia Kim, 2019. "Differences of Restorative Effects While Viewing Urban Landscapes and Green Landscapes," Sustainability, MDPI, vol. 11(7), pages 1-19, April.
    2. Helena Nordh & Caroline M. Hagerhall & Kenneth Holmqvist, 2013. "Tracking Restorative Components: Patterns in Eye Movements as a Consequence of a Restorative Rating Task," Landscape Research, Taylor & Francis Journals, vol. 38(1), pages 101-116, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yu Wu & Zhixiong Zhuo & Qunyue Liu & Kunyong Yu & Qitang Huang & Jian Liu, 2021. "The Relationships between Perceived Design Intensity, Preference, Restorativeness and Eye Movements in Designed Urban Green Space," IJERPH, MDPI, vol. 18(20), pages 1-16, October.
    2. Suling Guo & Wei Sun & Wen Chen & Jianxin Zhang & Peixue Liu, 2021. "Impact of Artificial Elements on Mountain Landscape Perception: An Eye-Tracking Study," Land, MDPI, vol. 10(10), pages 1-18, October.
    3. Brzoska, P. & Grunewald, K. & Bastian, O., 2021. "A multi-criteria analytical method to assess ecosystem services at urban site level, exemplified by two German city districts," Ecosystem Services, Elsevier, vol. 49(C).
    4. Youngeun Kang & Eujin Julia Kim, 2019. "Differences of Restorative Effects While Viewing Urban Landscapes and Green Landscapes," Sustainability, MDPI, vol. 11(7), pages 1-19, April.
    5. Xiaohuan Xie & Hanzhi Zhou & Zhonghua Gou & Ming Yi, 2021. "Spatiotemporal Patterns of the Use of Green Space by White-Collar Workers in Chinese Cities: A Study in Shenzhen," Land, MDPI, vol. 10(10), pages 1-25, September.
    6. Massimiliano Masullo & Francesca Castanò & Roxana Adina Toma & Luigi Maffei, 2020. "Historical Cloisters and Courtyards as Quiet Areas," Sustainability, MDPI, vol. 12(7), pages 1-21, April.
    7. 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.
    8. Mengyun Wu & Yu Gao & Zhi Zhang & Bo Zhang & Huan Meng & Weikang Zhang & Tong Zhang, 2023. "How Do Repeated Viewings in Forest Landscapes Influence Young People’s Visual Behaviors and Cognitive Evaluations?," IJERPH, MDPI, vol. 20(6), pages 1-25, March.
    9. Yujia Zhai & Binbin Fan & Jingyao Yu & Ruoyu Gong & Jie Yin, 2024. "Effects of Spatial Type and Scale of Small Urban Open Spaces on Perceived Restoration: An Online Survey-Based Experiment," Land, MDPI, vol. 13(9), pages 1-17, August.
    10. Massimiliano Masullo & Asli Ozcevik Bilen & Roxana Adina Toma & Gulsen Akin Guler & Luigi Maffei, 2021. "The Restorativeness of Outdoor Historical Sites in Urban Areas: Physical and Perceptual Correlations," Sustainability, MDPI, vol. 13(10), pages 1-23, May.
    11. Yilin Sun & Li Zhu & Jiang Li & Ni Zhang & Yue Tang & Xiaokang Wang & Honglin Wu, 2023. "Study on the Influence and Optimization of Neighborhood Space on the Perceived Restoration of Rural Left-Behind Older People: The Case of Changsha, China," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    12. Yangyang Shi & Jiao Zhang & Xinyue Shen & Liang Chen & Yunchen Xu & Rui Fu & Yang Su & Yiping Xia, 2022. "Designing Perennial Landscapes: Plant Form and Species Richness Influence the Gaze Perception Associated with Aesthetic Preference," Land, MDPI, vol. 11(10), pages 1-17, October.
    13. Chang Li & Xiaohui Huang, 2022. "Differences in Visual Attraction between Historical Garden and Urban Park Walking Scenes," Land, MDPI, vol. 11(10), pages 1-16, October.
    14. Xuan Zhang & Haoying Han & Lin Qiao & Jingwei Zhuang & Ziming Ren & Yang Su & Yiping Xia, 2022. "Emotional-Health-Oriented Urban Design: A Novel Collaborative Deep Learning Framework for Real-Time Landscape Assessment by Integrating Facial Expression Recognition and Pixel-Level Semantic Segmentat," IJERPH, MDPI, vol. 19(20), pages 1-20, October.
    15. Peng Wang & Wenjuan Yang & Dengju Wang & Youjun He, 2021. "Insights into Public Visual Behaviors through Eye-Tracking Tests: A Study Based on National Park System Pilot Area Landscapes," Land, MDPI, vol. 10(5), pages 1-19, May.
    16. Marjan Shayestefar & Mahdieh Pazhouhanfar & Clarine van Oel & Patrik Grahn, 2022. "Exploring the Influence of the Visual Attributes of Kaplan’s Preference Matrix in the Assessment of Urban Parks: A Discrete Choice Analysis," Sustainability, MDPI, vol. 14(12), pages 1-19, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:7:p:3799-:d:777873. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.