Inspiring Social Capital Through Community Green Space: Pathways and Implications
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YE Lin is an associate professor in the Faculty of Architecture and Urban Planning, Chongqing University, and a member of the Key Laboratory of New Technology for Construction of Cities in Mountain Area, Ministry of Education. His research focuses on urban and rural ecological planning, and urban green space planning |
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HE Shi is a master student in the Faculty of Architecture and Urban Planning, Chongqing University. Her research focuses on urban green space planning |
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LI Yinghao is a master student of Faculty of Architecture and Urban Planning Chongqing University. His research focuses on urban green space planning |
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YAN Zhaohui, Master, is director of and a professorate senior engineer in the No. 1 Planning Branch of the General Research Institute of Architecture & Planning Design Co., Ltd., Chongqing University. His research focuses on urban and rural ecological planning |
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HUANG Lei, Master, is deputy director of the No. 1 Planning Branch of the General Institute of Architecture & Planning Design Co., Ltd., Chongqing University. His research focuses on urban and rural ecological planning |
Received date: 2024-06-27
Revised date: 2025-02-16
Online published: 2025-12-14
Copyright
Objective The evolution of urban community governance in China has progressed through three distinct historical phases: The danwei (work unit) system under planned economy, the neighborhood committee system during market reform, and the current community-based governance model. These institutional transformations have fundamentally reshaped social relationship patterns, eroding traditional kinship-based connections and resulting in fragmented community networks and a continuous decline in residents’ sense of belonging. In recent years, urban renewal strategies have shifted from singular focus on physical space renovation to integrated approaches that actively cultivate social capital — collective assets embedded in social networks, mutual trust, and shared behavioral norms. Across Chinese cities, green space development initiatives (particularly community gardens and urban agriculture programs) are increasingly positioned as dual-purpose interventions that bridge physical environment improvement with social relationship reconstruction, often serving as neutral grounds for conflict resolution and collective identity formation. While these projects demonstrate potential in enhancing community cohesion and resident well-being, persistent challenges exist regarding sustainable operation funding models , quantifiable social outcomes, and equitable access across socioeconomic groups. Under China’s precision governance paradigm emphasizing data-driven policymaking, this research systematically investigates the operational mechanisms through which community green spaces inspire social capital, incorporating both grassroots practices and institutional innovations, based on which evidence-based optimization strategies for urban renewal practices are proposed. Methods This research combines visual mapping analysis based on CitieSpace software with a number of inductive and deductive review methods. The process involves three main stages. The first stage uses CitieSpace to analyze global research patterns by studying countries with largest research output and tracking changes in key research topics over time. The second stage carefully examines existing research to identify common research methods, areas of agreement among scholars, and ongoing debates in the field. The third stage creates a focused collection of studies that specifically explore how green spaces create social benefits, with a focus on the following three aspects: How people connect socially, how trust develops between community members, and how shared community rules form. For the data collection phase, English-language articles published between January 2000 and October 2023 are gathered from the Web of Science database using search terms related to social connections and green spaces. The search strategy is TS = (“social capital*” OR “social network”) AND (“green space*” OR “garden” OR “park”). The research selects 63 articles that clearly link green spaces to community social benefits after removing duplicate entries and unrelated research. After a thorough evaluation, the research selects 32 articles specifically explaining how green spaces foster social connections for final analysis. Results Geographical distribution analysis reveals concentrated research output from Western countries: The United States contributes 22 studies (34.9%), followed by Canada (8), Australia (5), and the United Kingdom (4), collectively representing 72% of total publications. Temporal keyword evolution identifies three developmental stages: The early phase (2000–2010) emphasized macro-level urban green infrastructure planning and public health outcomes; the middle phase (2010–2018) shifted focus to micro-level community gardens as mental health interventions and food security solutions; the current phase (post-2018) explores multifunctional green spaces as social capital incubators within precision governance frameworks. Researchers generally agree on four main findings. First, green spaces act as important gathering places that encourage social interaction. Second, the interaction of social networks, trust, and norms is facilitated by social interactions in green spaces. Third, higher quality green spaces tend to support stronger community relationships. Fourth, how people perceive and experience these spaces matters more than their physical characteristics alone. However, debates continue about whether the social benefits created in green spaces spread to other parts of the community and whether they reach all community groups equally. Conclusion The research identifies three primary ways community green spaces help build social connections. The first involves creating different types of social networks — strengthening bonds among similar groups, building bridges between different groups, and connecting people across social levels. The second focuses on developing trust through safer spaces and neighborly cooperation. The third centers on turning shared experiences in green spaces into formal community guidelines that guide how spaces are planned, used, and maintained. Building on these findings and considering current practices in Chinese community projects, three key recommendations emerge. The first suggests combining local community resources with outside support to create networks of shared interest. The second proposes starting with small-scale green space projects to build trust and maintain community engagement over time. The third emphasizes involving residents directly in managing green spaces to turn collective experiences into established community practices. These strategies aim to help communities better integrate social connection-building into green space development efforts while addressing ongoing challenges in project sustainability and effectiveness. Three prospective research directions are proposed based on the deficiencies and trends in international research: Enhancing the mechanisms through which green spaces cultivate social capital, identifying critical factors that affect social capital to guide the augmentation of the social impact of community green spaces; examining the disparities in green space requirements among various demographics; and investigating community governance strategies informed by green space interventions. Owing to regional disparities, pertinent research must be integrated with the current circumstances of community revitalization and governance in China, tackling genuine challenges and prospective development objectives.
YE Lin , HE Shi , LI Yinghao , YAN Zhaohui , HUANG Lei . Inspiring Social Capital Through Community Green Space: Pathways and Implications[J]. Landscape Architecture, 2025 , 32(4) : 79 -88 . DOI: 10.3724/j.fjyl.202406270351
| 网络 类型 | 网络开放性 | 成员社会 地位特征 | 连结 强弱 | 社会网络特征 | 典型活动 |
|---|---|---|---|---|---|
| 结合型 | 同质性 | 水平关系 | 强关系 | 具有较强烈的认同感以及共同目标,它能够促进成员间的承诺与互惠 | 家庭亲子活动、亲戚交往活动等 |
| 桥接型 | 异质性 | 弱关系 | 拥有共同利益者所形成的联结,能够促进相对异质之人群或团体间的联系与互动 | 邻居间的园艺互助、分享交流会、联欢会等 | |
| 链接型 | 异质性 | 垂直关系 | 弱关系 | 建立不同社会层级的个人或团体之间的关系,透过与不同层级之间的联结,从正式体制中获得讯息和资源 | 街道、社区居委会、业委会组织的社区会议、选举活动等 |
表2 发文量前10的国家Tab. 2 Top 10 countries in terms of publication volume |
| 数量 | 中心值 | 首次出现年份 | 国家 |
|---|---|---|---|
| 22 | 0.08 | 2005 | USA(美国) |
| 7 | 0 | 2004 | Canada(加拿大) |
| 7 | 0 | 2011 | Australia(澳大利亚) |
| 6 | 0.01 | 2011 | UK(英国) |
| 4 | 0.01 | 2014 | Germany(德国) |
| 4 | 0.01 | 2019 | Japan(日本) |
| 3 | 0 | 2019 | China(中国) |
| 3 | 0.02 | 2021 | Iran(伊朗) |
| 3 | 0 | 2014 | Netherlands(荷兰) |
| 2 | 0 | 2022 | Finland(芬兰) |
| 2 | 0 | 2021 | Poland(波兰) |
表3 讨论社区绿色空间促生社会资本的文献[16, 24, 27-34, 40-42, 45-63]Tab. 3 Literature on social capital inspiration through green space[16, 24, 27-34, 40-42, 45-63] |
| 序号 | 研究方法 | 空间载体 | 涉及要素 | 国家 | 发表年月 | 参考文献 | ||
|---|---|---|---|---|---|---|---|---|
| 社会网络 | 社会信任 | 社会规范 | ||||||
| 1 | 叙事分析 | 社区花园 | √ | 美国 | 2004年4月 | [24] | ||
| 2 | 焦点小组访谈 | 社区花园 | √ | √ | 圣马力诺 | 2005年12月 | [47] | |
| 3 | 问卷调查 | 街区交叉口 | √ | √ | 美国 | 2009年1月 | [48] | |
| 4 | 分层线性和逻辑回归分析 | 社区花园 | √ | √ | 美国 | 2010年5月 | [45] | |
| 5 | 焦点小组访谈、相关性分析 | 贫民窟麻袋园艺 | √ | 肯尼亚 | 2013年9月 | [28] | ||
| 6 | 焦点小组访谈 | 贫民窟绿色空间 | √ | 印度 | 2014年4月 | [27] | ||
| 7 | 相关性分析 | 邻里树冠层 | √ | √ | 美国 | 2015年6月 | [49] | |
| 8 | 半结构化访谈、主题分析 | 社区花园 | √ | √ | 澳大利亚 | 2018年4月 | [34] | |
| 9 | 多元线性回归模型分析 | 社区花园 | √ | √ | 德国 | 2018年4月 | [50] | |
| 10 | 相关性分析 | 绿地 | √ | 美国 | 2018年6月 | [32] | ||
| 11 | 重复测量的纵向研究 | 贫民窟家庭花园 | √ | √ | 秘鲁 | 2018年8月 | [51] | |
| 12 | 问卷调查 | 家庭花园和社区花园 | √ | 澳大利亚 | 2018年9月 | [52] | ||
| 13 | 问卷调查、相关性分析 | 社区花园 | √ | 美国 | 2018年10月 | [53] | ||
| 14 | 半结构化访谈、焦点小组、 主题分析 | 社区花园 | √ | 美国 | 2018年12月 | [54] | ||
| 15 | 问卷调查,半结构化访谈 | 社区花园 | √ | √ | 新西兰 | 2019年2月 | [55] | |
| 16 | 半结构化访谈、问卷调研 | 社区花园 | √ | √ | 丹麦 | 2019年3月 | [56] | |
| 17 | 半结构化访谈、归纳演绎分析 | 城市绿道 | √ | 加拿大 | 2019年10月 | [29] | ||
| 18 | 半结构化访谈、主题分析 | 社区花园 | √ | √ | 澳大利亚 | 2020年3月 | [33] | |
| 19 | 回归模型分析 | 社区花园 | √ | 美国 | 2020年10月 | [57] | ||
| 20 | 半结构化访谈 | 社区花园 | √ | 美国 | 2020年11月 | [42] | ||
| 21 | 因子分析和回归分析 | 社区花园 | √ | 中国 | 2020年12月 | [30] | ||
| 22 | 文本分析 | 分配花园 | √ | 英国 | 2021年2月 | [58] | ||
| 23 | 相关性分析 | 城市公园 | √ | 伊朗 | 2021年3月 | [31] | ||
| 24 | 社会网络分析法 | 森林景观和退化土地 | √ | √ | √ | 伊朗 | 2021年9月 | [59] |
| 25 | 结果分析、线性回归分析 | 城市绿道 | √ | 爱尔兰 | 2021年12月 | [60] | ||
| 26 | 多元线性模型分析 | 公共空间 | √ | √ | 英国 | 2022年6月 | [61] | |
| 27 | 相关性分析 | 社区绿地 | √ | 新加坡 | 2022年11月 | [16] | ||
| 28 | 开放式访谈 | 社区花园 | √ | √ | √ | 美国 | 2022年12月 | [41] |
| 29 | 半结构化访谈、主题分析 | 社区花园 | √ | 英国 | 2023年1月 | [62] | ||
| 30 | 半结构化访谈、归纳演绎分析 | 社区农业 | √ | 巴西 | 2023年1月 | [40] | ||
| 31 | 多智能体模拟分析 | 城市公地 | √ | 荷兰 | 2023年2月 | [63] | ||
| 32 | 半结构化访谈 | 城市花园 | √ | √ | 加拿大 | 2023年4月 | [46] | |
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