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Effects of Spatial Elements of Urban Landscape Forests on the Restoration Potential and Preference of Adolescents

Author

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  • Linjia Wu

    (College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China)

  • Qidi Dong

    (College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China)

  • Shixian Luo

    (Graduate School of Horticulture, Chiba University, Chiba 263-8522, Japan)

  • Wenyuan Jiang

    (College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China)

  • Ming Hao

    (College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China)

  • Qibing Chen

    (College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China)

Abstract

City green space can promote people’s health and aesthetic satisfaction; however, most extant research focuses on suburban forests and urban parks. Urban landscape forests have important ecological and aesthetic value for urban environments. This study conducted a visual stimulation to examine the impact of four common spatial element combinations in urban landscape forests on teenagers’ recovery potential and preference. The results indicate that urban landscape forests had positive physiological and psychological effects on adolescents, including decreased blood pressure, improved heart rate, reduced anxiety, and improved recovery ability. Diastolic blood pressure relief performance was better among males than females. In addition, a stepwise linear regression analysis was performed to explore the quantitative relationship between spatial elements and recovery and preference values. The results demonstrate that water elements were a significant predictor in the quantitative relationship between spatial elements in landscape forests and restoration and preference values. Terrain, flower, and shrub elements did not have a significant effect on overall restoration and preference values. This study highlights the intervention value of urban landscape forests in promoting the health and well-being of adolescents, with implications for future planning and design of urban landscape forests.

Suggested Citation

  • Linjia Wu & Qidi Dong & Shixian Luo & Wenyuan Jiang & Ming Hao & Qibing Chen, 2021. "Effects of Spatial Elements of Urban Landscape Forests on the Restoration Potential and Preference of Adolescents," Land, MDPI, vol. 10(12), pages 1-16, December.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:12:p:1349-:d:697080
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    References listed on IDEAS

    as
    1. Bieling, Claudia, 2014. "Cultural ecosystem services as revealed through short stories from residents of the Swabian Alb (Germany)," Ecosystem Services, Elsevier, vol. 8(C), pages 207-215.
    2. Bieling, Claudia & Plieninger, Tobias & Pirker, Heidemarie & Vogl, Christian R., 2014. "Linkages between landscapes and human well-being: An empirical exploration with short interviews," Ecological Economics, Elsevier, vol. 105(C), pages 19-30.
    3. Jing Xie & Shixian Luo & Katsunori Furuya & Dajiang Sun, 2020. "Urban Parks as Green Buffers During the COVID-19 Pandemic," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    4. Giergiczny, Marek & Czajkowski, Mikołaj & Żylicz, Tomasz & Angelstam, Per, 2015. "Choice experiment assessment of public preferences for forest structural attributes," Ecological Economics, Elsevier, vol. 119(C), pages 8-23.
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    Cited by:

    1. Linjia Wu & Qidi Dong & Shixian Luo & Yanling Li & Yuzhou Liu & Jiani Li & Zhixian Zhu & Mingliang He & Yuhang Luo & Qibing Chen, 2022. "An Empirical Study of the Restoration Potential of Urban Deciduous Forest Space to Youth," IJERPH, MDPI, vol. 19(6), pages 1-20, March.
    2. Henry Lippert & Ingo Kowarik & Tanja M. Straka, 2022. "People’s Attitudes and Emotions towards Different Urban Forest Types in the Berlin Region, Germany," Land, MDPI, vol. 11(5), pages 1-21, May.
    3. 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.
    4. Xiaojia Liu & Xi Chen & Yan Huang & Weihong Wang & Mingkan Zhang & Yang Jin, 2023. "Landscape Aesthetic Value of Waterfront Green Space Based on Space–Psychology–Behavior Dimension: A Case Study along Qiantang River (Hangzhou Section)," IJERPH, MDPI, vol. 20(4), pages 1-22, February.

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