Exploring the spatial relationship between urban built environment and green travel: An improved semi-parametric GWR approach

Abstract

Public transit and non-motorized travel offer numerous environmental, social and public health benefits.Existing literature focus on the correlation between the built environment and green travel in metropolitan centers, with limited studies on suburban new towns, essential for comprehensive urban expansion and sustainable development. This paper examines the effect of the built environment on public transit and non-motorized travel by using point of interest data and household economic data from Jiading District, Shanghai. An innovative framework is introduced, based on the geographically weighted regression model, which captures spatial heterogeneity while balancing the inequality and directionality of different areas in the transportation network. The results demonstrate that the proposed improved semi-parametric geographically weighted regression outperforms the traditional geographically weighted regression model in evaluation capabilities. A distinct spatial heterogeneity in travel patterns is identified between central and peripheral areas. The densely populated central zones exhibit a preference for intra-district travel, often opting for non-motorized modes due to their convenience and health benefits while peripheral areas serve as crucial connectors, facilitating long-distance travel within the metropolitan area through public transit and multimodal transportation. Regional transportation infrastructure construction and socioeconomic factors also affect the choice of green travel. The findings could provide theoretical references and policy implications to the development of green transportation and urban sustainability.