数字城市时空分析与可持续规划设计

这是疫情后城市规划中最紧迫的课题，城市研究人员可以为此做出贡献。2022年3月至5月上海发生封锁事件后，核酸检测采样点位急需时空优化，以保护公共资源，为各个社区提供更好的服务。为此，我实验室与上海大数据中心进行了相关研究，并形成了题为《上海核酸检测采样点时空优化》的报告。

科研项目

上海核酸检测采样点时空优化

上海核酸检测采样点时空优化

科研成果

  1. Guan, C., Yan, K., Zhang, B., Li, Y., & Zhang, X. (2023) The Efficacy of Mortgage Lending on Geographically Disparate and Differently Priced Residential Neighborhoods in Shanghai. The Professional Geographer (SSCI) https://doi.org/10.1080/00330124.2022.2148902  
  2. Guan, C., Wang, Y., Keith, M., Li, Y., Cao, G. (2022) Does local planning of fast-growing medium-sized towns lead to higher urban intensity or to sprawl? Cases from Zhejiang Province. Cities 130, 103869 (SSCI) https://doi.org/10.1016/j.cities.2022.103869
  3. Cai, Z., Guan, C.*, Trinh, A., Zhang, B., Chen, Z., Srinivasan, S., Nielsen, C. (2022) How to leverage urban residents’ satisfactions on self-perceived health? Neighborhood social and built environment effects in Chengdu, China. Sustainability 14(20), 13389. (SSCI) https://doi.org/10.3390/su142013389
  4. Bogdanowicz, A., Guan, C.* (2022) Public sentiment during the COVID-19 pandemic: Dynamic topic modeling of Twitter data in the United States. PLOS ONE (SCIE) https://doi.org/10.1371/journal.pone.0268669
  5. Guan, C.*, Tan, J., Hall, B., Liu, C., Li, Y., Cai, Z. (2022) The effect of the built environment on the COVID-19 pandemic at the initial stage: a county level study of the United States. Sustainability 14(6), 3417. (SCI & SSCI) https://doi.org/10.3390/su14063417
  6. Shi, Y., Yang, J. Keith, M., Song, K., Li, Y., Guan, C.*. (2022) Spatial accessibility patterns to public hospitals in Shanghai: An improved gravity model. The Professional Geographer 74(2), 265-289. (SSCI) https://doi.org/10.1080/00330124.2021.2000445
  7. Yao, Z., Yang, J., Liu, J., Keith, M., Guan, C.* (2021) Comparing Tweet sentiment in megacities using machine learning techniques: In the midst of COVID-19. Cities 116, 103273. (SSCI) https://doi.org/10.1016/j.cities.2021.103273
  8. Liu, C., Liu, Z., Guan, C. (2021) The impacts of the built environment on the incidence rate of COVID-19: A case study of King County, Washington. Sustainable Cities & Society 74, 103144 (SCI) https://doi.org/10.1016/j.scs.2021.103144
  9. Guan, C.*, Rowe, P. (2021) Beyond big versus small: assessing spatial variation of urban neighborhood block structures in high‑density cities. Socio-Ecological Practice Research 3, 37-53. (CNKI) https://doi.org/10.1007/s42532-021-00074-7
  10. Guan, C.*, Tan, J., Peiser, R. (2021) Spatiotemporal effects of proximity to metro extension on housing price dynamics in Manhattan, New York City. Journal of Transport and Land Use 14(1) 1295-1315. (SSCI) https://doi.org/10.5198/jtlu.2021.1915
  11. Guan, C.* and Forsyth, A. (2020) The influence of urban form and socio-demographics on active transport: A 40-neighborhoods study in Chengdu, China. Journal of Transport and Land Use, 13(1), 367-388. (SSCI) https://doi.org/10.5198/jtlu.2020.1697
  12. Guan, C.*, Srinivasan, S., Zhang, B., Da, L., Liu, J., Nielsen, C. (2020) The influence of neighborhood types and accessibility on active transport in China’s growing cities. Transportation Research Part D: Transport and Environment, 80, 102273. (SCI&SSCI) https://doi.org/10.1016/j.trd.2020.102273
  13. Srinivasan, S., Guan, C.*, Nielsen, C. (2020) Built environment, income and travel behavior: Change in the city of Chengdu, China 2005-2016. International Journal of Sustainable Transportation 14:10, 749-760. (SSCI) https://doi.org/10.1080/15568318.2019.1625088
  14. Guan, C. (2019) Spatial distribution of high-rise buildings and its relationship to public transit development in Shanghai. Transport Policy 81, 371-380. (SSCI)  https://doi.org/10.1016/j.tranpol.2018.09.004
  15. Guan, C.*, Srinivasan, S., Nielsen, C. (2019) Does neighborhood form influence low-carbon transportation in China? Transportation Research Part D: Transport and Environment 67, 406-420. (SCI&SSCI) https://doi.org/10.1016/j.trd.2018.12.015
  16. Guan, C.*, Keith, M., Hong, A., Wang, Y. (2019) Designing walkable cities and neighborhoods in the era of urban big data. Urban Planning International 34 (5) 9-15. DOI:10.22217/upi.2019.389
  17. Guan, C.*, Peiser, R. (2018) Accessibility, urban form, and property value: A study of Pudong, Shanghai. Journal of Transport and Land Use, 11(1) 1057-1080. (SSCI) http://dx.doi.org/10.5198/jtlu.2018.1318
  18. Guan, C.*, Rowe, P. (2016). The concept of urban intensity and China’s townization policy: Cases from Zhejiang Province. Cities, 55, 22-41. (SSCI) https://doi.org/10.1016/j.cities.2016.03.012