Characterizing the urban spatial structure using taxi trip big data and implications for urban planning

Many cities evolve over time, but some are designed from scratch. Brasília is presented as a unique case on urban planning for having been built from figuratively nothing, based on a design concept that was the brainchild of Brazilian urbanist Lucio Costa. The present study aimed to analyze the interrelation between urban planning and spatial structure change over time to understand the role of urban development policies on the spatial organization of Brasília. The study was conducted based on three interrelated aspects: (1) The intentions of the plans, (2) territorial governance, and (3) external conditions. The results showed that the circumstances of territory occupation—characterized by a polycentric development system with dispersed satellite cities economically dependent on Brasília—have been gradually replaced by strategic development policies, mainly influenced by social and political driving forces. Accordingly, this research suggests a reconsideration of the scale of development instrumentations based on a better understanding of the metropolitan area of Brasília as a unique structure by strengthening its interrelations and seeking better coordination of interests and adaptability of governance processes.

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Simulation Based Urban Spatial Structure Evolution and New Town's Development for Urban Planning

2011 Fourth International Conference on Intelligent Computation Technology and Automation ◽

10.1109/icicta.2011.231 ◽

2011 ◽

Author(s):

Chen Hongxia

Keyword(s):

Urban Planning ◽

Spatial Structure ◽

Structure Evolution ◽

Urban Spatial Structure ◽

Simulation Based

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A tale of two cities: Jobs–housing balance and urban spatial structures from the perspective of transit commuters

Environment and Planning B Urban Analytics and City Science ◽

10.1177/2399808320938803 ◽

2020 ◽

pp. 239980832093880

Author(s):

Jie Huang ◽

Yujie Hu ◽

Jiaoe Wang ◽

Xiang Li

Keyword(s):

Urban Planning ◽

Spatial Structure ◽

Urban Form ◽

Distribution Patterns ◽

Comparative Approach ◽

Urban Spatial Structure ◽

Spatial Structures ◽

Land Use Patterns ◽

Functional Zones ◽

Transit Network Design

The jobs–housing balance and urban spatial structure are naturally connected, and understanding the connection is important for urban planning, geography, and transport studies. Using smartcard data in Beijing and Shanghai, this research employs a comparative approach to reveal spatial distribution patterns of jobs–housing balance in terms of transit commuters and derive the implied urban spatial structures for the two megacities in China. Results suggested that (1) the overall job–resident ratios estimated with smartcard data were 1.97 and 2.47 in Shanghai and Beijing, respectively; (2) compared to Beijing, Shanghai had greater intermixing of jobs and housing; (3) Beijing’s urban form followed a concentric spatial structure, whereas Shanghai followed a quasi-sector configuration. These findings show that the job–resident ratio can be used as an indicator to capture land-use patterns or functional zones, which is useful for urban planning and transit network design.

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Revealing Characteristics of the Spatial Structure of Megacities at Multiple Scales with Jobs-Housing Big Data: A Case Study of Tianjin, China

Land ◽

10.3390/land10111144 ◽

2021 ◽

Vol 10 (11) ◽

pp. 1144

Author(s):

Ruixi Dong ◽

Fengying Yan

Keyword(s):

Big Data ◽

Spatial Structure ◽

Urban Space ◽

Dynamic Characteristics ◽

Multiple Scales ◽

Spatial Scales ◽

Urban Land Use ◽

Urban Spatial Structure ◽

Static Characteristics ◽

Transportation Development

Urban spatial structure reflects the organization of urban land use and is closely related to the travel patterns of residents. The characteristics of urban spatial structure include both static and dynamic aspects. The static characteristics of urban spatial structure reflect the morphological features of space, and the dynamic characteristics of urban spatial structure reflect intra-city functional linkages. With the continuous agglomeration of population and industries; megacities have become the core spatial carriers leading China’s social and economic development; and their urban spatial structure has also been reconstructed. However; there is still a certain lack of understanding of the characteristics of the spatial structure of China’s megacities. This study aimed to reveal characteristics of the spatial structure of Chinese megacities at different scales using jobs-housing big data. To achieve this goal, spatial autocorrelation and a geographically weighted regression (GWR) model were applied to reveal static polycentricity, and community detection was used to reveal dynamic commuting communities. The distribution of jobs in urban space and jobs–housing balance levels in commuting communities were further analyzed. Experiments were conducted in Tianjin, China. We found that: (1) the static characteristics of the spatial structure of megacities presented the coexistence of polycentricity and a high degree of dispersion at macro- and meso-scales; (2) the dynamic characteristics of the spatial structure of megacities revealed two types of commuting communities at macro- and meso-scales and most commuting communities had a good jobs-housing balance. These findings can be referenced by urban managers and planners to formulate relevant policies for spatial distribution optimization of urban functions and transportation development at different spatial scales.

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