公园城市目标下多类别公园生态系统文化服务感知与评估——以成都市中心城区为例

Perception and Assessment of Cultural Ecosystem Services in Multi-category Park under Park CityObjectives: A Case on the Central City of Chengdu

关键词:  风景园林  公园城市  生态系统文化服务  城市公园  公众感知  IPA分析

Key words:  landscape architecture  park city  cultural ecosystem services (CESs)  urban park  public perception  Importance-Performance Analysis (IPA)

摘要:

城市公园在为居民提供生态系统文化服务(CES)方面发挥着至关重要的作用。成都作为公园城市示范区，通过创新布局全域公园体系，推动公园形态与 城市空间深度融合。然而，不同类别公园的CES表现尚未得到全面评估，亟须根据公园特征分类施策，推动生态价值转化。以成都市中心城区4种类型的143个典 型公园为研究对象，爬取2013—2023年大众点评网用户评论数据，基于词频统计结果与Word2vec词嵌入模型构建城市公园CES评估框架，采用词频分析、相 关性分析、情感倾向分析及重要性－满意度(IPA)分析，量化多类别城市公园CES的感知差异与供需匹配情况。基于分析结果，剖析各类CES间的关联性和互补 性，针对多类别公园在评估中呈现的突出问题提出差异化策略

Abstract:

Urban parks play a pivotal role in delivering cultural ecosystem services (CES) to residents, significantly enhancing urban livability, social cohesion, and human well-being. These services encompass recreational opportunities, aesthetic enjoyment, spiritual enrichment, and cultural identity, all of which contribute to the sustainable development of cities. As a leading demonstration zone for the "Park City" initiative, Chengdu has pioneered an innovative citywide park system. This ambitious initiative has successfully achieved a profound integration between expansive park landscapes and the intricate fabric of urban spaces, fundamentally reshaping the urban experience. However, despite this significant progress, a critical knowledge gap persists: the dominant CES functions of different park categories have not yet been comprehensively assessed. Consequently, there is an urgent need for targeted strategies, meticulously crafted based on the inherent characteristics and primary functions of each park category, to effectively facilitate the transformation of ecological value into tangible societal benefits. Addressing this research imperative, this study focuses on the central urban area of Chengdu, selecting 143 typical parks representative of four major classification types. To capture public perceptions of CES, we collected a decade-long dataset (2013–2023) of user-generated reviews from Public Comments (Da Zhong Dian Ping), a prominent Chinese platform for location-based feedback. Leveraging advanced natural language processing techniques, we constructed a robust CES evaluation framework by combining word frequency statistics with the Word2vec word embedding model. This methodological approach allowed us to systematically categorize and quantify CES indicators, ensuring a nuanced understanding of how different park types are perceived by visitors. In addition, we also used word frequency analysis, correlation analysis, affective tendency analysis, and importance-satisfaction (IPA) analysis to quantify the perception of CES in different perceived differences in CES of different types of urban parks. In the future, based on the results of the analysis, the correlation and complementarity between CES can be utilized to focus on the weaknesses and deficiencies in the supply of cultural services in different types of parks, and to differentiate the focus on the dimensions of planning and positioning, landscape design, and facility configuration.