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Multidimensional Visual Preferences and Sustainable Management of Heritage Canal Waterfront Landscape Based on Panoramic Image Interpretation

Author

Listed:
  • Xin Jiang

    (College of Horticulture, Nanjing Agricultural University, Nanjing 211800, China)

  • Xin Li

    (School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

  • Mingrui Wang

    (School of Architecture, Tsinghua University, Beijing 100084, China)

  • Xi Zhang

    (College of Arts, Tianjin University of Technology, Tianjin 300384, China)

  • Wenhai Zhang

    (Graduate School of Creative Science and Engineering, Waseda University, Tokyo 169-8555, Japan)

  • Yongjun Li

    (College of Horticulture, Nanjing Agricultural University, Nanjing 211800, China)

  • Xin Cong

    (College of Horticulture, Nanjing Agricultural University, Nanjing 211800, China)

  • Qinghai Zhang

    (College of Horticulture, Nanjing Agricultural University, Nanjing 211800, China)

Abstract

As an important type of linear cultural heritage and a waterfront landscape that integrates both artificial and natural elements, heritage canals provide the public with a multidimensional perceptual experience encompassing aesthetics, culture, and nature. There remains a lack of refined, micro-level studies on heritage canal landscapes from a multidimensional perspective of visual preference. This study focuses on a typical segment of the Grand Canal in China, specifically the ancient canal section in Yangzhou. We employed SegFormer image semantic segmentation techniques to interpret features from 150 panoramic images, quantitatively identifying the waterfront environmental characteristics of the heritage canal. Four perceptual dimensions were constructed: aesthetic preference, cultural preference, natural preference, and hydrophilic preference. Through a questionnaire survey and various statistical analyses, we revealed the relationships between visual preferences for the waterfront landscape of heritage canals and environmental characteristics. The main findings of the study include the following: (1) Aesthetic preference is positively correlated with cultural, natural, and hydrophilic preferences, while natural preference shows a negative correlation with cultural and hydrophilic preferences. (2) Aesthetic preference is influenced by a combination of blue-green natural elements and artificial factors. Natural preference is primarily affected by increased vegetation visibility, cultural preference is associated with a higher proportion of cultural facilities and high-quality pavements, and hydrophilic preference is linked to larger water surface areas, fewer barriers, and better water quality. (3) There are spatial differences in canal waterfront landscape preferences across different urban areas, with the old city exhibiting higher aesthetic, cultural, and hydrophilic preferences than the new city and suburban areas. Finally, this study proposes strategies for optimising and enhancing the quality of waterfront landscapes of heritage canals, aiming to provide sustainable practical guidance for the future planning and management of these heritage sites.

Suggested Citation

  • Xin Jiang & Xin Li & Mingrui Wang & Xi Zhang & Wenhai Zhang & Yongjun Li & Xin Cong & Qinghai Zhang, 2025. "Multidimensional Visual Preferences and Sustainable Management of Heritage Canal Waterfront Landscape Based on Panoramic Image Interpretation," Land, MDPI, vol. 14(2), pages 1-25, January.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:2:p:220-:d:1573283
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    References listed on IDEAS

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    1. Jiao Zhang & Danqing Li & Shuguang Ning & Katsunori Furuya, 2023. "Sustainable Urban Green Blue Space (UGBS) and Public Participation: Integrating Multisensory Landscape Perception from Online Reviews," Land, MDPI, vol. 12(7), pages 1-29, July.
    2. Yiwen Li & Bing Qiu, 2024. "Using Deep Learning Approaches to Quantify Landscape Preference of the Chinese Grand Canal: An Empirical Case Study of the Yangzhou Ancient Canal," Sustainability, MDPI, vol. 16(9), pages 1-19, April.
    3. Rong Fan & Ken P. Yocom & Yeyuan Guo, 2023. "Utilizing Fractal Dimensions as Indicators to Detect Elements of Visual Attraction: A Case Study of the Greenway along Lake Taihu, China," Land, MDPI, vol. 12(4), pages 1-21, April.
    4. Xie, Bo & Pang, Zhe & He, Dongsheng & Lu, Yi & Chen, Yujie, 2023. "Effects of neighborhood environment on different aspects of greenway use: Evidence from East Lake Greenway, China," Journal of Transport Geography, Elsevier, vol. 106(C).
    5. Shuying Zhang & Wenting Yu, 2024. "Canal Heritage Tourism Utilization Models: Experience and Inspirations from the Grand Canal (Beijing Section)," Land, MDPI, vol. 13(6), pages 1-22, June.
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