CN 11-5366/S     ISSN 1673-1530
“风景园林,不只是一本期刊。”
邵钰涵,卢慧霖.基于多源数据的社区公园游憩规律及其空间特征关联研究:以上海为例[J].风景园林,2024,31(2):32-40.
引用本文: 邵钰涵,卢慧霖.基于多源数据的社区公园游憩规律及其空间特征关联研究:以上海为例[J].风景园林,2024,31(2):32-40.
SHAO Y H, LU H L. Research on Correlation Between Recreation Rules and Spatial Features of Community Parks Based on Multi-Source Data: A Case Study of Shanghai[J]. Landscape Architecture, 2024, 31(2): 32-40.
Citation: SHAO Y H, LU H L. Research on Correlation Between Recreation Rules and Spatial Features of Community Parks Based on Multi-Source Data: A Case Study of Shanghai[J]. Landscape Architecture, 2024, 31(2): 32-40.

基于多源数据的社区公园游憩规律及其空间特征关联研究以上海为例

Research on Correlation Between Recreation Rules and Spatial Features of Community Parks Based on Multi-Source Data: A Case Study of Shanghai

  • 摘要:
    目的 对社区公园进行精细化游憩规律分类,并探索游憩规律与空间特征的关系,对社区公园游憩效率的提升具有指导意义。
    方法 对上海市中心城区110个社区公园进行研究,基于手机信令数据,识别社区公园绿地周期游憩活跃规律并进行频谱聚类;结合多源数据,提取区域功能、交通可达性和公园空间特征并与游憩到访率进行关联。
    结果 社区公园日周期游憩规律可分为单波峰活跃型和多波峰活跃型2类,包括晨间、午间、晚间波峰活跃型和早晚间、中下午、中晚间波峰活跃型,活跃类型与周边用地功能呈现直接关联。游憩到访率与空间特征要素的关联中,总体与周边空间商业用地占比、公交站点密度、道路密度呈现强相关,不同游憩活跃类型中也各呈现出与公共管理用地占比、绿地可达性、公园面积、硬质景观占比等指标的相关性。
    结论 各游憩活跃类型的绿地游憩效率提升应结合游憩规律考虑不同的指标,例如中晚间波峰活跃型绿地宜更加关注绿地可达性、硬质活动场地的面积等。这些发现为研究城市社区公园游憩时空行为、精准提升社区公园服务水准提供了新视角。

     

    Abstract:
    Objective The growing demand for meticulous green space allocation has made the intensive utilization of urban community parks an imperative nowadays. Nonetheless, prevailing community park planning tends to be expansive and lacks the adept integration of efficiency nuances arising from diverse usage behaviors. The classification of recreational patterns within community parks, coupled with an exploration of their correlation with spatial features, presents substantial potential for precisely steering the augmentation of recreational efficiency in community parks
    Methods This research conducts a comprehensive investigation encompassing 110 community parks in Shanghai. Leveraging location based service (LBS) data, the research identifies patterns of recreational activities within community parks across distinct time periods. Employing spectral clustering based on visit frequency, peak counts, and peak time periods, the research amalgamates data from diverse sources, including built environment data and urban transportation data. The primary objective is to extract three pivotal feature categories: regional functionality, transportation accessibility, and green space features. These features undergo meticulous scrutiny for their correlation with recreational visit efficiency. Regional functional features encompass parameters such as proportion of industrial land, public management and service land, residential land, transportation land, and commercial land, and the functional mix of parkland. Transportation accessibility features comprise metrics such as green space accessibility, bus stop density, and road network density. Green space features include park area, green coverage, hard surface ratio, and water area proportion. The synthesis of these features provides a nuanced understanding of the factors influencing recreational visit efficiency in community parks.
    Results The recreational activity patterns in community parks are successfully categorized into single-peak and multi-peak types, including morning, noon, and evening peak activity types, as well as morning and evening, noon and afternoon, and noon and evening peak activity types. These patterns exhibit a direct association with the surrounding land use functions. In the analysis of spatial features influencing recreational visit efficiency in community parks, the research finds a strong correlation of recreational visit efficiency with the overall percentage of commercial land, bus stop density, and road density. Additionally, different recreational activity types show significant correlations with the proportion of public management land, green space accessibility, park area, and hard surface ratio. For instance, the recreational visit frequency of morning peak activity types is correlated with the mix of functions around the park, while the recreational visit frequency of noon peak activity types is related to green space accessibility, park area, and hard surface ratio. The recreational visit frequency of evening peak activity types is correlated with the mix of functions around the park and road network density. The recreational visit frequency of morning and evening peak activity types is more related to the proportion of public management and service land, green space accessibility, bus stop density, and park area. The recreational visit frequency of noon and afternoon peak activity types is more related to the proportion of commercial land and bus stop density. The recreational visit frequency of noon and evening peak activity types is correlated with green space accessibility and hard surface ratio.
    Conclusion To enhance recreational visit efficiency, it is crucial to consider different indicators based on recreational patterns. For community parks with morning and evening peak activities, strategies such as strengthening surrounding public management and service functions, optimizing transportation accessibility and bus stop density, and refining park area are recommended. Conversely, for community parks with evening peak activities, placing more emphasis on green space accessibility and the area of hard activity surfaces may be more suitable. The research further reveals that surrounding functionality plays a key role in determining people’s behavioral tendencies, with commercial functionality significantly influencing overall efficiency and providing daily recreational activities for surrounding residents. The enhancement of functional diversity has a greater impact on morning and evening peak activity types. Moreover, adequate bus station facilities, a sparse road network, and high accessibility are considered factors that promote the use of green space parks. The layout of a small road network is crucial for the accessibility of evening active walking. In terms of planning and design, it is recommended to consider the rational layout of surrounding road networks to facilitate walking and reduce dependence on transportation. This is especially important during the evening peak and noon to evening peak periods when people typically prefer walking. Providing convenient walking paths and facilities can alleviate traffic congestion and improve travel efficiency. Additionally, it is suggested to fully consider supporting services such as surrounding bus stations, especially in communities with early evening commuting peaks and afternoon recreation needs. The research also indicates that larger park area may contribute to the increased visit efficiency of green spaces during noon and evening peak activity types. Therefore, in areas with busy midday and evening pedestrian traffic, providing sufficient space is essential. The research further provides directions for precisely improving recreational visit efficiency in community parks, such as offering ample children’s games and health and fitness facilities for midday and evening peak activity types, which are crucial for improving the usage paths of such activity types. These findings offer a new perspective for researching the temporal and spatial behaviors of urban community green spaces, thus providing insights for the precise enhancement of community green space services.

     

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