Identification of Urban Spatial Form Based on Multimode Transit Travel Features
Publication: Journal of Urban Planning and Development
Volume 149, Issue 3
Abstract
The daily trips of urban residents in different transport modes reflect the urban mobility pattern and the latent spatial structure of the city, which is seldom addressed in the literature. A network-based cluster model is applied in this paper based on multimode transit big data. Thus, the urban spatial form can be observed at different levels according to the travel modes and distance, differing from traditional geographic structures. This paper will identify the urban mobility pattern and the corresponding spatial form by taking the Beijing metropolitan area as a study area. Origin–destination data at the traffic analysis zone level were collected, covering shared bike, bus, and metro. The results show that the metro trips reflect the single-center feature of Beijing. However, the multicenter development trend can be revealed by bus and shared-bike data. This paper finds that shared bike supports the establishment of subcenters as a new transport mode. The urban spatial form presents a complex feature of multiple levels and spatial diversity due to the comprehensive effect of multiple travel modes. The study results can provide a basis for the planning of transit network and urban equilibrium land use and development.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (5197082625) and National Science Foundation of Beijing Municipality (9202012).
References
Aguiléra, V., S. Allio, V. Benezech, F. Combes, and C. Milion. 2014. “Using cell phone data to measure quality of service and passenger flows of Paris transit system.” Transp. Res. Part C: Emerging Technol. 43: 198–211. https://doi.org/10.1016/j.trc.2013.11.007.
Akin, D., and S. Alasalvar. 2016. “Estimate urban growth and expansion by modeling urban spatial structure using hierarchical cluster analyses of interzonal travel data.” Int. J. Syst. Dyn. Appl. 5 (4): 16–41.
Bohlin, L., D. Edler, A. Lancichinetti, and M. Rosvall. 2014. Community detection and visualization of networks with the map equation framework, 3–34. Cham, Switzerland: Springer.
Bracken, I., and D. Martin. 1989. “The generation of spatial population distributions from census centroid data.” Environ. Plann. A: Econ. Space 21 (4): 537–543. https://doi.org/10.1068/a210537.
BTI (Beijing Transport Institute). 2018. “Beijing Transport Annual Report.” Accessed January 9, 2022. https://www.bjtrc.org.cn/List/index/cid/7.html.
Cai, B., H. Wang, H. Zheng, and H. Wang. 2011. “An improved random walk based clustering algorithm for community detection in complex networks.” In Proc., IEEE Int. Conference on Systems. New York: IEEE.
Cai, J., B. Huang, and Y. Song. 2017. “Using multi-source geospatial big data to identify the structure of polycentric cities.” Remote Sens. Environ. 202: 210–221. https://doi.org/10.1016/j.rse.2017.06.039.
Clark, C. 1951. “Urban population densities.” J. R. Stat. Soc. A 114 (4): 490. https://doi.org/10.2307/2981088.
Dantzig, G. B. 1973. “The ORSA New Orleans address on compact city.” Manag. Sci. 19 (10): 1151–1161. https://doi.org/10.1287/mnsc.19.10.1151.
Duany, A., and E. Plater-Zyberk. 1992. “The second coming of the American small town.” The Wilson Quarterly 16 (1): 3–51.
De Montis, A., S. Caschili, and A. Chessa. 2013. “Commuter networks and community detection: A method for planning sub regional areas.” Eur. Phys. J. Spec. Top. 215 (1): 75–91. https://doi.org/10.1140/epjst/e2013-01716-4.
Duan, Y. M., Y. Liu, X. H. Liu, and H. L. Wang. 2018. “Identification of polycentric urban structure of central Chongqing using points of interest big data.” J. Nat. Resour. 33 (5): 788–800.
Fang, C., X. Yu, X. Zhang, J. Fang, and H. Liu. 2020. “Big data analysis on the spatial networks of urban agglomeration.” Cities 102: 102735. https://doi.org/10.1016/j.cities.2020.102735.
Fellini, S., P. Salizzoni, L. Soulhac, and L. Ridolfi. 2019. “Propagation of toxic substances in the urban atmosphere: A complex network perspective.” Atmos. Environ. 198: 291–301. https://doi.org/10.1016/j.atmosenv.2018.10.062.
Fortunato, S. 2009. “Community detection in graphs.” Phys. Rep. 486 (3): 75–174.
Greene, D. L. 1980. “Recent trends in urban spatial structure.” Growth Change 11 (1): 29–40. https://doi.org/10.1111/j.1468-2257.1980.tb00427.x.
Hai, X., Y. Liu, P. Zhao, and H. Zhang. 2020. “Using mobile phone data to estimate the temporal-spatial distribution and socioeconomic attributes of population in megacities: A case study of Beijing.” Acta Sci. Nat. Univ. Pekinensis 56 (3): 518–530.
Hu, L., J. Yang, T. Yang, Y. Tu, and J. Zhu. 2020. “Urban spatial structure and travel in China.” J. Plann. Lit. 35: 6–24. https://doi.org/10.1177/0885412219853259.
Ismiyati, I., and F. Hermawan. 2018. “Lifestyle as an influential factor to urban mobility transport: A case study of Semarang City, Indonesia.” IOP Conf. Ser.: Earth Environ. Sci. 123: 012020. https://doi.org/10.1088/1755-1315/123/1/012020.
Li, X., and M. J. Edirisinghe. 2002. “Controlled synthesis of silicon carbide-aluminum nitride composites using a pre-ceramic polymer route.” J. Mater. Sci. Lett. 21 (6): 21–23. https://doi.org/10.1023/A:1014226108112.
Liu, X., B. Derudder, and M. Wang. 2018. “Polycentric urban development in China: A multi-scale analysis.” Environ. Plann. B: Urban Anal. City Sci. 45 (5): 953–972. https://doi.org/10.1177/2399808317690155.
Lv, T. 2013. “Research on the change of residents’ commuting characteristics based on the spatial evolution of metropolitan suburbs.” College of Automobile and Traffic Engineering, Nanjing Forestry Univ.
Lynch, K. 1981. “The form of the city.” In Cities and city planning. Boston: Springer.
Ma, J., J. C. P. Cheng, F. Jiang, W. Chen, and J. Zhang. 2020. “Analyzing driving factors of land values in urban scale based on big data and non-linear machine learning techniques.” Land Use Policy 94: 104537. https://doi.org/10.1016/j.landusepol.2020.104537.
Ma, J., J. Fan, F. Liu, and H. Li. 2019. “A community detection algorithm based on Markov random walks ants in complex network.” J. Shanghai Jiaotong Univ. (Sci.) 24 (1): 71–77. https://doi.org/10.1007/s12204-019-2041-2.
Matsumoto, H. 2004. “International urban systems and air passenger and cargo flows: Some calculations.” J. Air Transp. Manage. 10 (4): 239–247. https://doi.org/10.1016/j.jairtraman.2004.02.003.
Matsunaka, R., T. Oba, N. Dai, M. Nagao, and J. Nawrocki. 2013. “International comparison of the relationship between urban structure and the service level of urban public transportation—A comprehensive analysis in local cities in Japan, France and Germany.” Transp. Policy 30 (Nov.): 26–39. https://doi.org/10.1016/j.tranpol.2013.06.008.
McDonald, J. F. 1987. “The identification of urban employment subcenters.” J. Urban Econ. 21 (2): 242–258. https://doi.org/10.1016/0094-1190(87)90017-9.
McDonald, J. F., and P. J. Prather. 1994. “Suburban employment centres: The case of Chicago.” Urban Stud. 31 (2): 201–218. https://doi.org/10.1080/00420989420080201.
McMillen, D. P. 2001. “Nonparametric employment subcenter identification.” J. Urban Econ. 50 (3): 448–473. https://doi.org/10.1006/juec.2001.2228.
Meng, Y., X. Tian, Z. Li, W. Zhou, Z. Zhou, and M. Zhong. 2020. “Exploring node importance evolution of weighted complex networks in urban rail transit.” Physica A 558: 124925. https://doi.org/10.1016/j.physa.2020.124925.
Niu, X., L. Ding, and X. Song. 2015. “Understanding urban spatial structure of Shanghai central city based on mobile phone data.” China City Plann. Rev. 24 (3): 15–23.
Pan, H., B. Deal, Y. Chen, and G. Hewings. 2018. “A reassessment of urban structure and land-use patterns: Distance to CBD or network-based?— Evidence from Chicago.” Reg. Sci. Urban Econ. 70: 215–228. https://doi.org/10.1016/j.regsciurbeco.2018.04.009.
Pan, Y., Y. Tian, X. Liu, D. Gu, and G. Hua. 2016. “Urban big data and the development of city intelligence.” Engineering 2 (2): 171–178. https://doi.org/10.1016/J.ENG.2016.02.003.
Pons, P., and M. Latapy. 2006. “Computing communities in large networks using random walks.” J. Graph Algorithms Appl. 10 (2): 191–218. https://doi.org/10.7155/jgaa.00124.
Rodrigue, J.-P., C. Comtois, and B. Slack. 2009. The geography of transport systems. London: Routledge.
Rosvall, M., D. Axelsson, and C. T. Bergstrom. 2009. “The map equation.” Eur. Phys. J. Spec. Top. 178 (1): 13–23. https://doi.org/10.1140/epjst/e2010-01179-1.
Rosvall, M., and C. T. Bergstrom. 2008. “Maps of information flow reveal community structure in complex networks.” Proc. Natl. Acad. Sci. USA 105: 1118–1123. https://doi.org/10.48550/arXiv.0707.0609.
Roth, C., S. M. Kang, M. Batty, and M. Barthélemy. 2011. “Structure of urban movements: Polycentric activity and entangled hierarchical flows.” PLoS One 6 (1): e15923. https://doi.org/10.1371/journal.pone.0015923.
Sobolevsky, S., M. Szell, R. Campari, T. Couronné, Z. Smoreda, and C. Ratti. 2013. “Delineating geographical regions with networks of human interactions in an extensive set of countries.” PLoS One 8 (12): e81707. https://doi.org/10.1371/journal.pone.0081707.
Stevens, F. R., A. E. Gaughan, C. Linard, and A. J. Tatem. 2015. “Disaggregating census data for population mapping using random forests with remotely-sensed and ancillary data.” PLoS ONE 10 (2): e0107042.
Sun, Y., L. Mburu, and S. Wang. 2016. “Analysis of community properties and node properties to understand the structure of the bus transport network.” Physica A 450: 523–530. https://doi.org/10.1016/j.physa.2015.12.150.
Tardiff, T. J., T. N. Lam, and B. F. Odell. 1978. “Effects of employment and residential location choices on urban structure: A dynamic stochastic simulation.” Transp. Res. Rec. 673: 87–93.
Thiemann, C., F. Theis, D. Grady, R. Brune, and D. Brockmann. 2010. “The structure of borders in a small world.” PLoS One 5 (11): e15422. https://doi.org/10.1371/journal.pone.0015422.
Toole, J. L., M. Ulm, D. Bauer, and M. C. Gonzalez. 2012. “Inferring land use from mobile phone activity.” In Proc., ACM SIGKDD Int. Workshop on Urban Computing, 1–8. New York: ACM.
Tu, W., T. Zhu, J. Xia, Y. Zhou, Y. Lai, J. Jiang, and Q. Li. 2020. “Portraying the spatial dynamics of urban vibrancy using multisource urban big data.” Comput. Environ. Urban Syst. 80: 101428. https://doi.org/10.1016/j.compenvurbsys.2019.101428.
Verhetsel, A., I. Thomas, and M. Beelen. 2007. “Commuting behaviour in the Belgian metropolises or the power of the Alonso–Muth model.” In World Conf. on Transport Research. Washington, DC: The National Academies of Sciences, Engineering, and Medicine.
Wang, Z., H. Liu, Y. Zhu, Y. Zhang, A. Basiri, B. Büttner, X. Gao, and M. Cao. 2021. “Identifying urban functional areas and their dynamic changes in Beijing: Using multiyear transit smart card data.” J. Urban Plann. Dev. 147 (2): 04021002. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000662.
Wei, S., W. Zheng, and L. Wang. 2021. “Understanding the configuration of bus networks in urban China from the perspective of network types and administrative division effect.” Transp. Policy 104: 1–17. https://doi.org/10.1016/j.tranpol.2021.02.002.
Xin, Y., Z. Q. Xie, and J. Yang. 2016. “An adaptive random walk sampling method on dynamic community detection.” Expert Syst. Appl. 58 (Oct.): 10–19. https://doi.org/10.1016/j.eswa.2016.03.033.
Xu, J., A. Li, D. Li, Y. Liu, Y. Du, T. Pei, T. Ma, and C. Zhou. 2017. “Difference of urban development in China from the perspective of passenger transport around spring festival.” Appl. Geogr. 87: 85–96. https://doi.org/10.1016/j.apgeog.2017.07.014.
Xue, X., R. Zhang, X. Zhang, R. J. Yang, and H. Li. 2015. “Environmental and social challenges for urban subway construction: An empirical study in China.” Int. J. Project Manage. 33 (3): 576–588. https://doi.org/10.1016/j.ijproman.2014.09.003.
Yu, W., H. Bai, J. Chen, and X. Yan. 2019. “Analysis of space-time variation of passenger flow and commuting characteristics of residents using smart card data of Nanjing metro.” Sustainability 11 (18): 4989. https://doi.org/10.3390/su11184989.
Yuan, J., Y. Zheng, and X. Xie. 2012. “Discovering regions of different functions in a city using human mobility and POIs.” In Proc., 18th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, 186–194. New York: ACM.
Zhang, Y., C. Li, and J. Huang. 2019. “Research on the characteristics of job and housing space in Beijing based on multi-source data fusion.” Urban Dev. Res. 26 (12): 37–45.
Zhong, C., S. M. Arisona, X. Huang, M. Batty, and G. Schmitt. 2014. “Detecting the dynamics of urban structure through spatial network analysis.” Int. J. Geogr. Inf. Sci. 28 (11): 2178–2199. https://doi.org/10.1080/13658816.2014.914521.
Zhou, P., and X. L. Xiao. 2018. “Urban spatial structure of Hunan province from the perspective of space flow—Based on tencent location big data and Baidu index analysis.” Chin. Overseas Archit. 10: 80–84.
Zhou, Q., H. Lu, and W. Xu. 2007. “Comparison and analysis of urban resident trip characteristics.” J. Cent. South Highway Eng. 32 (2): 145–149.
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Published In
Journal of Urban Planning and Development
Volume 149 • Issue 3 • September 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Apr 5, 2022
Accepted: Apr 10, 2023
Published online: Jun 6, 2023
Published in print: Sep 1, 2023
Discussion open until: Nov 6, 2023
ASCE Technical Topics:
- Bicycles
- Data analysis
- Engineering fundamentals
- Highway transportation
- Infrastructure
- Methodology (by type)
- Public transportation
- Research methods (by type)
- Traffic analysis
- Traffic engineering
- Transportation engineering
- Transportation management
- Travel modes
- Travel patterns
- Urban and regional development
- Urban areas
- Vehicles
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