Exploring Associations between Street Networks and Cycling from the Perspective of Space Syntax: An Empirical Research of Yangpu District of Shanghai
Date
2019
Authors
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
AESOP
Abstract
Research on the correlation between physical activity such as walking and cycling and the built environment has received extensive attention. Based on how the built environment causes travel, most of the existing research focuses on spatial features such as land use, scale, density, and location on different geographic scales. The street networks is the largest and most obvious global space that affects the movement of residents. However, few studies pay attention to the influence of the structural characteristics of the street network on physical activity, thus ignoring how individuals are affected by the surrounding space elements in the process of movement. According to the theory of spatial syntax, the individual movement in the urban space network is caused by the space network itself under the same conditions, which means that the spatial configuration of the street network is a decisive factor for the movement pattern. Therefore, this paper, taking Yangpu District of Shanghai as an example, uses Mobike (a biking sharing service provider) location data to analyze the impact of urban spatial morphological characteristics on cycling. Firstly, the spatial network model of street space, which is based on the notion of a ‘segment map is established by spatial syntax, and the variables such as connectivity, integration and depth are used to characterize the spatial topological features of networks. Then, the time-space characteristics of the distribution of residents' cycling activities are analyzed by using Mobike location data. Subsequently, a spearman correlation analysis was used to assess the correlation between cycling activity and street network morphological characteristic. Interestingly, this paper finds that the local morphological characteristics of the street network have more correlations with the use of bikes than the global features. The space syntax variable that is most strongly associated with bicycle use appears at a search radius of 700 meters.
Description
Keywords
cycling, Mobike, space syntax, spatial networks analysis