期刊
JOURNAL OF TRANSPORT GEOGRAPHY
卷 93, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jtrangeo.2021.103076
关键词
Travel behavior; Shanghai; Taxi trajectory; Urban structure; Network analysis
This article uses taxi trajectory data to explore the interaction among absolute space, relative space, and relational space in Harvey's framework using Structural Equation Modeling (SEM). The study highlights the importance of coordinating land use and travel demand in urban planning and development, and identifies a mismatch between urban mobility and the built environment in Shanghai, resulting in a transformation of the city's polycentric structure in absolute space to a single-node structure in relational space.
The nature of urban space has long-drawn geographers' interest and David Harvey's conceptual framework of multiple spaces (i.e., absolute, relative, and relational) within cities has been widely adopted and developed. With its high spatial and temporal resolution, geospatial big data plays an increasingly important role in our understanding of urban structure. Taxi trajectory data is particularly useful in travel purpose estimation and allows for more granular insights into urban mobility due to the door-to-door nature of these trips. This article utilizes taxi trajectory data and explores the interaction among absolute space, relative space, and relational space in Harvey's framework using Structural Equation Modeling (SEM). Through an empirical study of Shanghai's downtown area, this paper highlights the importance of Harvey's framework in understanding cities' dynamic structure and argues for changes in urban planning and development to better coordinate land use and travel demand. We find an insignificant relationship between relative and relational space in Shanghai due to a mismatch between urban mobility and the built environment. This mismatch concentrates the transportation flow near the city's core area, transforming the polycentric structure of Shanghai's built environment in absolute space to a single-node structure in relational space. After identifying the contributing factors to this problem in Shanghai, this article suggests combining Harvey's conceptual framework of multiple spaces with geospatial big data to inform planning strategies that address the challenges of rapid urbanization.
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