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Examining Commercial Center Accessibility Using a Modified 2SFCA method in Realistic Networks in Nanjing, China

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Abstract

The accessibility of commercial centers (CCs) is a topic of great concern to consumers and planners. However, current research is mostly limited to the accessibility of a single traffic mode or rough road network, which makes it difficult to reflect on the real travel situation of residents. Based on the two-step floating catchment area (2SFCA) method framework, we propose an extended method for analyzing the accessibility of CCs in different transportation modes, making it suitable for commercial geography research. The Baidu Map API is used to provide more accurate, convenient, and realistic data for reliable estimates to pinpoint underserved populations. The results can be summarized as follows: First, the multimode R2SFCA method proposed fills the knowledge gap to the accessibility of a single traffic mode or or rough road network. Second, there exist significant differences in the spatial distribution of access to CCs for consumers in different transportation modes. The range of public transit along metro or bus routes shows a finger-like spatial distribution, while car traffic extends along external urban traffic routes and is time-sensitive because of traffic conditions. Third, changes in the average accessibility scores for all travel modes showed similar patterns with increasing threshold time. These accessibility measures help identify underserved areas and enable the development of policy recommendations for the optimal allocation of commercial facilities and resources.

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Data Availability

The datasets generated during and/or analysed during the current study are not publicly available due to copyrights but are available from the corresponding author on reasonable request.

Notes

  1. The data set provided by Data Center for Resources and Environmental Sciences at the Chinese Academy of Sciences (RESDC) (http://www.resdc.cn) was aggregated in 1,000 m × 1,000 m cells, considering both the terrain and population density.

  2. http://www.mofcom.gov.cn/aarticle/b/g/201111/20111107814859.html

  3. http://www.nanjing.gov.cn/xxgk/szf/201609/t20160908_4145568.html

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Acknowledgements

This project was supported by the Natural Science Foundation of Anhui Province and Shanxi Datong University Research Startup Fund. We would like to express appreciations to colleagues in the laboratory for their constructive suggestions. Also, we thank the anonymous reviewers and members of the editorial team for their constructive comments.

Funding

This project was supported by the Natural Science Foundation of Anhui Province (2008085MD109), Key project of Department of Education of Anhui Province (K120439051) and Shanxi Datong University Research Startup Fund (2019-B-09).

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Authors and Affiliations

  1. School of Resources and Environmental Engineering, Anhui University, Anhui Province, Hefei, 230601, People’s Republic of China

    Jianhua Ni

  2. Anhui Province Key Laboratory of Wetland Ecosystem Protection and Restoration, Anhui University, Hefei, 230601, People’s Republic of China

    Jianhua Ni

  3. School of Architecture and Surveying Engineering, Datong University, Datong, Shanxi Province, 037009, People’s Republic of China

    Jie Chen

  4. School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu Province, 210023, People’s Republic of China

    Zheng Fu, Changbai Xi & Jiechen Wang

  5. Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing, Jiangsu Province, 210023, People’s Republic of China

    Jiechen Wang

  6. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing University, Nanjing, Jiangsu Province, 210023, People’s Republic of China

    Jiechen Wang

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  1. Jianhua Ni
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  2. Jie Chen
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  3. Zheng Fu
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  4. Changbai Xi
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Correspondence to Jiechen Wang.

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Ni, J., Chen, J., Fu, Z. et al. Examining Commercial Center Accessibility Using a Modified 2SFCA method in Realistic Networks in Nanjing, China. Netw Spat Econ 23, 1025–1045 (2023). https://doi.org/10.1007/s11067-023-09602-2

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  • DOI: https://doi.org/10.1007/s11067-023-09602-2

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