| 摘要: |
| 林荫道作为城市典型的绿色线性景观,对于优化城市生态环境及促进公众健康具有重要意义。为持续释放其生态与社会效益,开展林荫道景观质量综合
评估具有重要实践价值。以上海市104条林荫道为例,结合实地勘察与计算机视觉技术,构建一套基于“视觉-管理-健康”协同视角的林荫道质量评价体系。依
据评价结果对林荫道进行聚类分析,结果表明:上海市林荫道普遍绿量充足,空间围合感强且安全感知度高,树木健康状况良好,其中82.69%的林荫道综合景
观质量达到优良标准。结合林荫道在城市街道系统中的功能定位,识别出空间围合型、交通主导型、生态主导型、生活体验型及功能完善型5种空间模式,并针对
不同模式提出相应的管理优化策略。研究结果不仅可为城市林荫道的评价与类型划分提供有益参考,也为各类林荫道景观管护与品质提升提供重要实践指导 |
| 关键词: 风景园林 林荫道 景观质量 协同视角 聚类分析 |
| DOI:10.19775/j.cla.2026.09.0054 |
| 投稿时间:2024-10-12修订日期:2025-01-17 |
| 基金项目:上海市2023年度“科技创新行动计划”社会发展科技攻关项目(23DZ1204400) |
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| Research on the Evaluation and Classification of AvenueLandscape Quality from the Synergistic Perspective of "Visual-Management-Health" |
| HE Kun,,HUANG Yimeng,,YANG Ruiqing,,FENGShucheng,,LI Jie* |
| Abstract: |
| Avenues play a vital role in urban ecosystems by offering ecological
benefits like dust control, climate regulation, and stormwater management.
When integrated with other green infrastructure, avenues improve urban
resilience and environmental quality, benefiting residents' health and promoting
outdoor activities. This study evaluates 104 avenues in Shanghai, aiming to
develop a landscape quality evaluation system based on visual, management,
and tree health factors, and to identify avenue types using clustering methods.
The study surveyed 104 avenues across 16 districts using stratified random
sampling. Data on road images, management status, and tree growth were
collected, and an evaluation system was created, quantifying these factors with
deep learning models. K-means clustering categorized the avenues into five
types: space enclosure, traffic-dominated, ecological-dominated, life experience,
and functionally complete. Each type exhibits distinct characteristics in visual,
management, and tree health aspects. Results showed that 82.69% of avenues
were rated as good or above, with central urban areas scoring higher than
suburbs. Avenues generally feature dense shade, strong spatial enclosure, and
rich colors, though green view rates and recreational facilities need improvement.
Motor vehicle interference and overhead lines are well-managed, but ancillary
amenities require enhancement. Street trees display good health despite limited
planting conditions. This study provides a scientific basis for optimizing urban
avenue design and management, offering practical recommendations for
improving ecological and functional outcomes. |
| Key words: landscape architecture avenue landscape quality collaborative
perspective cluster analysis |