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Analysis of Beijing’s Working Population Based on Geographically Weighted Regression Model

Author

Listed:
  • Yanyan Chen

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China)

  • Hanqiang Qian

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China)

  • Yang Wang

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China)

Abstract

Evaluation of urban planning and development is becoming more and more important due to the large-scale urbanization of the world. With the application of mobile phone data, people can analyze the development status of cities from more perspectives. By using the mobile phone data of Beijing, the working population density in different regions was identified. Taking the working population density in Beijing as the research object and combining the land use of the city, the development status of Beijing was evaluated. A geographically weighted regression model (GWR) was used to analyze the difference in the impact of land use on the working population between different regions. By establishing a correlation model between the working population and land use, not only can the city’s development status be evaluated, but it can also help city managers and planners to make decisions to promote better development of Beijing.

Suggested Citation

  • Yanyan Chen & Hanqiang Qian & Yang Wang, 2020. "Analysis of Beijing’s Working Population Based on Geographically Weighted Regression Model," Sustainability, MDPI, vol. 12(12), pages 1-16, June.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:12:p:5018-:d:373679
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    References listed on IDEAS

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    1. Xingyuan Xiao & Minyue Hu & Minghong Tan & Xiubin Li & Wei Li, 2018. "Changes in the Ecological Footprint of Rural Populations in the Taihang Mountains, China," Sustainability, MDPI, vol. 10(10), pages 1-13, October.
    2. Xiang Zhou & Xiaohong Chen & Tianran Zhang, 2016. "Impact of Megacity Jobs-Housing Spatial Mismatch on Commuting Behaviors: A Case Study on Central Districts of Shanghai, China," Sustainability, MDPI, vol. 8(2), pages 1-22, January.
    3. Fan Yang & Fan Ding & Xu Qu & Bin Ran, 2019. "Estimating Urban Shared-Bike Trips with Location-Based Social Networking Data," Sustainability, MDPI, vol. 11(11), pages 1-14, June.
    4. Lingbo Liu & Zhenghong Peng & Hao Wu & Hongzan Jiao & Yang Yu & Jie Zhao, 2018. "Fast Identification of Urban Sprawl Based on K-Means Clustering with Population Density and Local Spatial Entropy," Sustainability, MDPI, vol. 10(8), pages 1-16, July.
    5. Lingbo Liu & Zhenghong Peng & Hao Wu & Hongzan Jiao & Yang Yu, 2018. "Exploring Urban Spatial Feature with Dasymetric Mapping Based on Mobile Phone Data and LUR-2SFCAe Method," Sustainability, MDPI, vol. 10(7), pages 1-15, July.
    6. Yanyan Chen & Zheng Zhang & Tianwen Liang, 2019. "Assessing Urban Travel Patterns: An Analysis of Traffic Analysis Zone-Based Mobility Patterns," Sustainability, MDPI, vol. 11(19), pages 1-15, October.
    7. Yingqi Guo & Shu-Sen Chang & Feng Sha & Paul S F Yip, 2018. "Poverty concentration in an affluent city: Geographic variation and correlates of neighborhood poverty rates in Hong Kong," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-17, February.
    8. Shaojun Liu & Ling Zhang & Yi Long, 2019. "Urban Vitality Area Identification and Pattern Analysis from the Perspective of Time and Space Fusion," Sustainability, MDPI, vol. 11(15), pages 1-27, July.
    9. Lingjun Tang & Yu Lin & Sijia Li & Sheng Li & Jingyi Li & Fu Ren & Chao Wu, 2018. "Exploring the Influence of Urban Form on Urban Vibrancy in Shenzhen Based on Mobile Phone Data," Sustainability, MDPI, vol. 10(12), pages 1-21, December.
    10. A. Stewart Fotheringham & Martin Charlton & Chris Brunsdon, 1997. "Measuring Spatial Variations in Relationships with Geographically Weighted Regression," Advances in Spatial Science, in: Manfred M. Fischer & Arthur Getis (ed.), Recent Developments in Spatial Analysis, chapter 4, pages 60-82, Springer.
    11. Lucas, Karen & Philips, Ian & Mulley, Corinne & Ma, Liang, 2018. "Is transport poverty socially or environmentally driven? Comparing the travel behaviours of two low-income populations living in central and peripheral locations in the same city," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 622-634.
    12. Meina Zheng & Feng Liu & Xiucheng Guo & Xinyue Lei, 2019. "Assessing the Distribution of Commuting Trips and Jobs-Housing Balance Using Smart Card Data: A Case Study of Nanjing, China," Sustainability, MDPI, vol. 11(19), pages 1-19, September.
    13. Jinjun Tang & Fan Gao & Fang Liu & Wenhui Zhang & Yong Qi, 2019. "Understanding Spatio-Temporal Characteristics of Urban Travel Demand Based on the Combination of GWR and GLM," Sustainability, MDPI, vol. 11(19), pages 1-19, October.
    14. Yaxiong Ma & Sucharita Gopal, 2018. "Geographically Weighted Regression Models in Estimating Median Home Prices in Towns of Massachusetts Based on an Urban Sustainability Framework," Sustainability, MDPI, vol. 10(4), pages 1-27, March.
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