基于“主体-客体”多维耦合模型的城市公园夜间使用模式识别与关联机制研究——以杭州主城区为例

A Study on the Recognition and Correlation Mechanism of Nighttime Use Patterns in Urban Parks Based on the Multidimensional Coupling Model of "Subject-Object": A Case Study of the Main Urban Area of Hangzhou

关键词:  风景园林  城市公园  夜间使用  “主体-客体”多维耦合

Key words:  landscape architecture  urban park  nighttime use  multidimensional coupling of subject-object

摘要:

公园作为兼具生态效益与社会效益的重要场所，其夜间空间使用与城市建成环境之间的关系尚未被重视。以人为主体、公园及其周边环境为客体，构建基于多源数据的夜间公园“主体-客体”多维度耦合模型，探讨城市公园的使用模式类型及其影响机制。结果表明：1)杭州主城区城市公园的夜间使用强度与服务范围随时间呈现异质性波动；2)城市公园的夜间使用模式可归纳为客体景观禀赋型、客体功能依附型、主体社群友好型、客体失活型和客体高活型五大典型集群；3)夜间公园的建成环境对其使用特征的影响主要体现在社会属性构成与使用强度上，其中公园面积、慢行交通可达性，以及居住小区与休闲娱乐设施等分布密度被识别为促进公园夜间使用的正向相关因子。研究结果可为未来公园城市建设提供启发，从主客交互角度对不同类型公园、不同使用时段、不同使用人群的使用特征进行精细化解析，为城市规划者和公园管理者的规划干预与政策制定提供参考依据。

Abstract:

With the accelerating pace of urbanization and the increasing diversification of modern urban lifestyles, urban night-time economies and night-time vitality are being fundamentally reshaped. Although urban parks serve as critical public spaces that support a wide range of activities and provide essential ecological and recreational functions, their nighttime spatial usage patterns and underlying mechanisms remain insufficiently examined. This study conceptualizes "night-time parks" as urban parks that are open to or used by the public during night-time hours, in which the parks and their surrounding built environment are framed as the "object" elements, while diverse user groups constitute the "subject". On this basis, a multidimensional subject-object coupling model is developed using multi-source data to identify the characteristics and mechanisms of night-time park use from twotype. Among these, the facility-dependent and landscape-endowment clusters are the two most prevalent categories, spatially concentrated in the urban core and suburban edge zones, respectively. Third, the built environment of parks exerts a substantial influence on user composition and activity intensity. Park size, pedestrian accessibility, and the density of residential neighborhoods and leisure facilities are identified as key positive correlates of night-time park use. Based on these findings, the study proposes a set of targeted planning and policy recommendations to optimize urban park configuration and enhance their night-time service functions: 1) Optimize public transport operations during evening peak hours by establishing customized routes that integrate multiple park nodes; 2) Adjust and improve critical built environment factors surrounding parks - guided by user demand surveys - to enhance night-time landscape quality and public service facilities; 3) Strengthen pedestrian connectivity between workplaces and park nodes, and optimize the spatial layout of commercial and recreational amenities along these routes. In conclusion, this research offers a fine-grained analytical framework for examining night-time park use through the lens of subject-object interaction, enabling the differentiated understanding of various park types, temporal usage patterns, and user groups. The findings provide both theoretical insights into the mechanisms of night-time park activity and practical guidance for urban planners and park managers in developing targeted spatial interventions and policy measures to improve the quality, inclusivity, and liveliness of night-time public spaces. complementary analytical dimensions: spatio-temporal coupling and attribute coupling. The spatio-temporal coupling dimension enables the identification of user groups during specific time periods, thereby forming the basis for establishing attribute linkages between subjects and objects. The attribute coupling dimension quantifies the distributional patterns of park indicators, providing direct evidence of the interrelationships between built environment factors and user behavior. Empirical analysis of urban parks in the main urban area of Hangzhou yields three key findings. First, the intensity and service coverage of nighttime park use display significant temporal heterogeneity, fluctuating across different time periods. Second, night-time usage patterns can be categorized into five typical clusters: object landscape-endowment type, object facility-dependent type, subject community-friendly type, object inactive type, and object highly active