Exploring the Associations Between Urban Form and Neighborhood Vibrancy: A Case Study of Chengdu, China

Abstract

The design and optimization of urban form has always been a hot topic in urban planning and development research. Besides, the creation of continuous vitality in urban areas is of critical importance in the development of urbanization. However, due to the lack of data, it is difficult to measure the effects of urban form on neighborhood vibrancy. Additionally, no uniform conclusion has been drawn regarding to what degree urban form can contribute to neighborhood vibrancy. Taking advantage of emerging new data sources, the depth and breadth of related research can now be improved. Therefore, this paper uses high-precision positioning social media check-in data to approximate the vibrancy of 658 neighborhoods, and uses a geographical information system (GIS) to quantitatively measure the urban form indicators in the central area of Chengdu City, China. A quantitative exploration and analysis of the relationships between neighborhood vibrancy and urban form is conducted. The results of three regression models considering different explanatory variables show that socio-economic factors account for approximately 23% of neighborhood vibrancy. In addition, the correlation between the shape characteristics of a neighborhood and the vibrancy is weak. However, when the inner urban form indicators of neighborhoods are introduced into the regression model, the goodness of fit (R2) is nearly doubled. This finding indicates that strong associations exist between urban form and neighborhood vibrancy. Specifically, building density and functional diversity are positively correlated with neighborhood vibrancy. Unlike existing studies, this study finds that the road network within the neighborhood plays a positive role in the creation of neighborhood vibrancy. However, the impact of a road density indicator is not as powerful as the impacts of building density and functional diversity. This research can help urban designers to better design urban environments.

Keywords

• urban form
• social media check-in data
• neighborhood vibrancy
• linear regression