Study on the distance from green space and social capital of community residents based on the development of smart city—take the city of Lansing as an example

This paper innovatively adopts an interdisciplinary method, which is urban design, combined with social investigation, statistical analysis, and case analysis. In this study, 1350 residents in 45 blocks of Lansing were selected as samples to investigate the related issues of social capital, which include safety, contact with others, and sense of support for people living in certain areas. There are two ways to measure the distance from the center of the community to the nearest green space. One is the straight distance, while the other is path distance. Through statistical analysis, the path distance of less than 250 m is also added into the variables. The results overturned the hypotheses and showed that the distance of green space was positively correlated with social capital. The residents of Lansing may prefer the distant green space for recreational activities and create a way to participate in civic duty. The research can not only provide a basis for Lansing to formulate the appropriate resource management rules and norms and promote the accumulation of residents' social capital, but also provide a reference for urban green space planning in other areas. At the same time, in the context of developing a smart city and constructing a new public system, we hope that the better optimization of the green space allocation will be achieved.

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Publication Details

Journal
Frontiers of Architectural Research
Published
2024-10-04
DOI
https://doi.org/10.1016/j.foar.2024.06.009
Primary Topic
Urban Green Space and Health
Type
article
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article

Study on the distance from green space and social capital of community residents based on the development of smart city—take the city of Lansing as an example

Yang Han, Dong Zheng, Xiaoxiao Wang, Jiezikang Zeng
Frontiers of Architectural Research
Urban Green Space and Health
article

Study on the distance from green space and social capital of community residents based on the development of smart city—take the city of Lansing as an example

Yang Han, Dong Zheng, Xiaoxiao Wang, Jiezikang Zeng
article en

Abstract

This paper innovatively adopts an interdisciplinary method, which is urban design, combined with social investigation, statistical analysis, and case analysis. In this study, 1350 residents in 45 blocks of Lansing were selected as samples to investigate the related issues of social capital, which include safety, contact with others, and sense of support for people living in certain areas. There are two ways to measure the distance from the center of the community to the nearest green space. One is the straight distance, while the other is path distance. Through statistical analysis, the path distance of less than 250 m is also added into the variables. The results overturned the hypotheses and showed that the distance of green space was positively correlated with social capital. The residents of Lansing may prefer the distant green space for recreational activities and create a way to participate in civic duty. The research can not only provide a basis for Lansing to formulate the appropriate resource management rules and norms and promote the accumulation of residents' social capital, but also provide a reference for urban green space planning in other areas. At the same time, in the context of developing a smart city and constructing a new public system, we hope that the better optimization of the green space allocation will be achieved.

Frontiers of Architectural ResearchVol. 14(1)
Macau University of Science and Technology (MO), Guangdong University of Technology (CN), Shunde Polytechnic (CN)
Sustainable cities and communities
Openalex Percentile: Top 76%
Urban Green Space and Health
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Study on the distance from green space and social capital of community residents based on the development of smart city—take the city of Lansing as an example — Yang Han, Dong Zheng, et al. · Frontiers of Architectural Research (2024) | TGRS Research Map | TGRS