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Detecting urban commercial patterns using a latent semantic information model: A case study of spatial-temporal evolution in Guangzhou, China

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  • Shili Chen
  • Haiyan Tao
  • Xuliang Li
  • Li Zhuo

Abstract

With rapid economic growth since the 21st century, cities in China have experienced considerable economic and social reconstruction. Driven by rapid industrialization, urban spatial structures are undergoing evolution and change. Therefore, this paper analyzes the processes and mechanisms associated with the evolution of the commercial spatial structure in Guangzhou after the financial crisis in 2008 based on both theoretical and empirical analyses. We use a Dirichlet multinomial regression (DMR) model to extract latent semantic information and determine urban functional areas from global positioning system (GPS) and point-of-interest (POI) data collected in Guangzhou in 2009 and 2013. In addition, we use movement patterns and POI data to identify the evolution of Guangzhou's commercial zones from 2009 to 2013. The results show that the urban commercial structure in Guangzhou gradually changed from a single-center model to a multi-center model with dispersed clusters and that the distribution of the entire spatial structure changed. Meanwhile, Guangzhou’s commercial structure not only varied over time but also exhibited specific geographical features. This paper demonstrates that the proposed method can clearly identify the boundary of the commercial area in Guangzhou and provides a valid spatial-temporal model of change in the city. Moreover, this study not only expounds the future development trends of the urban spatial structure in Guangzhou from a microcosmic perspective but also provides a scientific basis for clarifying the spatial locations and development advantages of urban functions within the city.

Suggested Citation

  • Shili Chen & Haiyan Tao & Xuliang Li & Li Zhuo, 2018. "Detecting urban commercial patterns using a latent semantic information model: A case study of spatial-temporal evolution in Guangzhou, China," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-20, August.
    • Handle: RePEc:plo:pone00:0202162
    DOI: 10.1371/journal.pone.0202162
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    References listed on IDEAS

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    Cited by:

    1. Minjin Lee & Hangil Kim & SangHyun Cheon, 2021. "A Network Approach to Revealing Dynamic Succession Processes of Urban Land Use and User Experience," Sustainability, MDPI, vol. 13(21), pages 1-16, October.
    2. Shili Chen & Wei Lang & Xun Li, 2022. "Evaluating Urban Vitality Based on Geospatial Big Data in Xiamen Island, China," SAGE Open, , vol. 12(4), pages 21582440221, October.
    3. Lin Qiao & Huiping Huang & Yichen Tian, 2019. "The Identification and Use Efficiency Evaluation of Urban Industrial Land Based on Multi-Source Data," Sustainability, MDPI, vol. 11(21), pages 1-17, November.

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