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Assessing Daily Urban Systems: A Heterogeneous Commuting Network Approach

  • Ann Verhetsel
  • Joris Beckers
  • Michiel De Meyere
Article

Abstract

Daily Urban Systems (DUSs) are not only an attractive concept for planning locations for jobs, housing, schools and retail, but also for managing services such as public transportation and health care. If we can match geographically demand and supply of goods and services, higher levels of spatial efficiency can be reached. Since 50 years most of the research delineating DUSs uses thresholds of commuting levels, thus identifying labor markets polarized towards central cities. Few research grasps the more recent complex interactions within metropolitan areas due to growth and decentralization of activities. In this paper, we use techniques of complex network theory, namely community detection, on nearly 4,500,000 Belgian commuting links to define DUSs. Secondly, we explore differences for DUSs by gender and by income group. The results confirm the usefulness of community detection techniques for delineating Daily Urban Systems. Commuting patterns of females and low and very low income commuters are geographically more restricted than those of male and high and very high income commuters.

Keywords

Daily urban system DUS Labor markets Commuting Gender Income group Community detection Louvain method Belgium 

Notes

References

  1. Adam A, Delvenne J-C, Thomas I (2017). Cartography of interaction fields in and around Brussels: commuting, moves and telephone calls. Brussels Studies 118Google Scholar
  2. Antikainen J, Vartiainen P (2005) Polycentricity in Finland: From Structure to Strategy. Built Environ 31(2):143–152CrossRefGoogle Scholar
  3. Beckers J, Thomas I, Vanoutrive T, Verhetsel A (2018) Logistics clusters, including inter-firm relations through community detection. Eur J Transp Infrastruct Res 18(2):178–195Google Scholar
  4. Beckers J, Vanhoof M, Verhetsel A (2017) Returning the particular: Understanding hierarchies in the Belgian logistics system. J Transp Geogr, Published online.  https://doi.org/10.1016/j.jtrangeo.2017.09.015
  5. Berry BJL, Goheen PG, Goldstein H (1969) Metropolitan Area Definition: A Re-evaluation of Concept and Statistical Practice. U.S. Bureau of the Census, WashingtonGoogle Scholar
  6. Blondel V, Guillaume J, Lambiotte R, Lefebvre E (2008) Fast unfolding of community hierarchies in large networks. Journal of Statistical Mechanics: Theory and Experiment 10:1–6.  https://doi.org/10.1088/1742-5468/2008/10/P10008 CrossRefGoogle Scholar
  7. Blondel V, Krings G, Thomas I (2010) Regions and borders of mobile telephony in Belgium and in the Brussels metropolitan zone. Brussels Studies 42Google Scholar
  8. Bretagnolle A, Pumain D, Vacchiani-Marcuzzo C (2009) The organisation of urban systems. In: Lane D, Pumain D, Van der Leeuw S, West G (Eds.), Complexity perspective in innovation and social change (pp. 197–220). SpringerGoogle Scholar
  9. Burger M, Meijers E, van Oort F (2014) Multiple perspectives on functional coherence: Heterogeneity and multiplexity in the Randstad. Tijdschr Econ Soc Geogr 105(4):444–464CrossRefGoogle Scholar
  10. Crane R (2007) Is There a Quiet Revolution in Women’s Travel? Revisiting the Gender Gap in Commuting. J Am Plan Assoc 73(3):298–316.  https://doi.org/10.1080/01944360708977979 CrossRefGoogle Scholar
  11. de Montis, A., Chessa, A., Campagna, M., Caschili, S., & Deplano, G. (2009). Complex Network Analaysis of Commuting. Recent Advances and a Research Agenda. In: Reggiani A, Nijkamp P (Eds.), Complextity and Sptaial Networks. SpringerGoogle Scholar
  12. Ducruet C, Beauguitte L (2014) Spatial Science and Network Science: Review and Outcomes of a Complex Relationship. Networks and Spatial Economics 14(3–4):297–316.  https://doi.org/10.1007/s11067-013-9222-6 CrossRefGoogle Scholar
  13. European Commission (2016) Atlas of the Human Planet 2016. Mapping Human Presence on Earth with the Global Human Settlement Layer, JRC Science for Policy Report. Publications Office of the European Union, LuxemburgGoogle Scholar
  14. Expert P, Evans T, Blondel V, Lambiotte R (2011) Uncovering space-independent communities in spatial networks. PNAS 108(19):7663–7668.  https://doi.org/10.1073/pnas.1018962108 CrossRefGoogle Scholar
  15. Farmer CJQ, Fotheringham AS (2005) Network-based functional regions. Environment and Planning A, 43(11)Google Scholar
  16. Fred ALN, Jain AK (2003) Robust data clustering. IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2:128–136Google Scholar
  17. Gimenez-Nadal JI, Molina AJ (2016) Commuting Time and Household Responsibilities: Evidence Using Propensity Score Matching. J Reg Sci 56(2):332–259CrossRefGoogle Scholar
  18. Grauwin S, Szell M, Sobolevsky S, Hövel P, Simini F, Vanhoof M et al (2017) Identifying the structural discontinuities of human interactions. Sci Rep 7(46677).  https://doi.org/10.1038/srep46677
  19. Guérois M, Pavard A, Bretagnolle A, Mathian H (2016) Méthode de délimitation des aires urbaines fonctionelles par les temps de transport: expertise sur trois métroploes européennes. Belgeo 2Google Scholar
  20. Guimerà R, Amaral LAN (2005) Functional cartography of complex metabolic networks. Nature 433(7028):895–900.  https://doi.org/10.1038/nature03288 CrossRefGoogle Scholar
  21. Hanssens H, Derudder B, van Aelst S, Witlox F (2014) Assessing the functional polycentricity of the mega-city-region of Central Belgium based on advanced producer service transaction links. Reg Stud 48(12):1939–1953CrossRefGoogle Scholar
  22. Helling A (2002) Transportation, land use, and the impacts of sprawl on poor and children and families. Urban Sprawl: Causes, Consequences, and Policy Responses, 119–140Google Scholar
  23. Kloosterman RC, Musterd S (2001) The Polycentric Urban Region: Towards a Research Agenda. Urban Stud 38(4):623–633CrossRefGoogle Scholar
  24. Lockhart PM, Vandermotten C (2009) Atlas des dynamiques territoriales - Les bassins d’emploi en Belgique (II). Atlas Des Dynamiques Territoriales Google Scholar
  25. McMillen DP (2001) Polycentric urban structure: The case of Milwaukee. Economic Perspectives-Federal Reserves Bank of Chicago 25(2):15–27Google Scholar
  26. Miller HJ (2017) Geographic information science II: Mesogeography. Prog Hum Geogr 42(2):600–609.  https://doi.org/10.1177/0309132517712154 CrossRefGoogle Scholar
  27. Nelson GD, Rae A (2016) An Economic Geography of the United States: From Commutes to Megaregions. PLoS One 11(11).  https://doi.org/10.1371/journal.pone.0166083
  28. Newman MEJ (2006) Modularity and Community Structure in Networks. Proceedings of the National Academy of Science of the United States of America 103(23):8577–8582.  https://doi.org/10.1073/pnas.0601602103 CrossRefGoogle Scholar
  29. Newman MEJ, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69(2).  https://doi.org/10.1103/PhysRevE.69.026113
  30. OECD (2013) Definition of Functional Urban Areas (FUA) for the OECD metropolitan database. ParisGoogle Scholar
  31. Patacchini, E., Zenou, Y., Vernon Henderson, J., & Epple, D. (2009). Urban Sprawl in Europe. In Brookings-Wharton Papers on urban Affairs (pp. 125–149). Brookings Institution PressGoogle Scholar
  32. Patuelli R, Reggiani A, Gorman SP, Nijkamp P, Bade F-J (2007) Network Analysis of Commuting Flows: A Comparative Static Approach to German Data. Networks and Spatial Economics 7(4):315–331CrossRefGoogle Scholar
  33. Powell J (2002) Sprawl, fragmentation, and the persistence of racial inequality: limiting civil rights by fragmenting space. Urban Sprawl: Causes, Consequences, and Policy Responses, 73–118Google Scholar
  34. Pumain D, Daint-Julien T, Cattan N, Rozenblat C (1992) The statistical concept of the town in Europe. Eurostat, LuxemburgGoogle Scholar
  35. Riguelle F, Thomas I, Verhetsel A (2007) Measuring urban polycentrism: A European case study and its implications. J Econ Geogr 7(2):193–215.  https://doi.org/10.1093/jeg/lbl025 CrossRefGoogle Scholar
  36. Roberts, J., Hodgson, R., & Dolan, P. (2009). It’s driving her mad: gender differences in the effects of commuting on psychological well-being. Department of Economics, University of SheffieldGoogle Scholar
  37. Schwanen T (2016) Geographies of Transport II : Reconciling the General and the Particular. Prog Hum Geogr 41(3):1–10.  https://doi.org/10.1177/0309132516628259 CrossRefGoogle Scholar
  38. So KS, Orazem PF, Otto DM (2001) The effects of housing prices, wages, and commuting time on joint residential and job location choices. Am J Agric Econ 83(4):1036–1048CrossRefGoogle Scholar
  39. Thévenon O (2013) Drivers of Female Labour Froce Participation in the OECD. Working Papers on Social Issues, Employment and Migration. ParisGoogle Scholar
  40. Thomas I, Adam A, Verhetsel A (2017) Migration and commuting interaction fields: A new geography with a community detection algorithm? Belgeo, 2017(4)Google Scholar
  41. United Nations (2016) The World’s Cities in 2016Google Scholar
  42. Van Der Haegen H, Pattyn M (1979) De Belgische stadsgewesten. Statistische En Econometrische Studieën 59Google Scholar
  43. van der Laan L (1998) Changing Urban Systems: An Empirical comparison of three alternative models. Reg Stud 32(3):235–247CrossRefGoogle Scholar
  44. van der Laan L, Schalke R (2001) Reality versus Policy: The Deliniation and Testing of Local Labour Market and Spatial Policy Areas. Eur Plan Stud 9(2):201–221CrossRefGoogle Scholar
  45. Van Hecke E, Halleux J-M, Decroly J-M, Mérenne-Schoumaker B (2007) Noyaux d’habitat et Régions urbaines dans une Belgique urbanisée. In Monographies Enquête Socioéconomique (p. 201). Bruxelles: SPF Economie en Politique Scientifique FédéraleGoogle Scholar
  46. Van Meeteren M, Boussauw K, Derudder B, Witlox F (2016) Flemish Diamond or ABC-Axis. The Spatial Structure of the Belgian metropolitan area. Eur Plan Stud 24(5):974–995CrossRefGoogle Scholar
  47. Van Nuffel N, Saey P (2005) Commuting, Hierarchy and Networking: the Case of Flanders. Tijdschr Econ Soc Geogr 96(3):313–327.  https://doi.org/10.1111/j.1467-9663.2005.00462.x CrossRefGoogle Scholar
  48. Van Ommeren J, van den Berg G, Gorter C (2000) Estimating the Marginal Willigness to Pay for Commuting. J Reg Sci 40(3):541–563CrossRefGoogle Scholar
  49. Vandekerckhove B, Van Damme L, Loris I (2014) Daily Urban Systems. Een onderzoek naar openbaarvervoeknooppunten als drager voor de ruimtelijke onwikkeling in Vlaanderen. Ruimte Jg Sept-Okt-Nov 23:80–85Google Scholar
  50. Vanderbiesen W, Jacobs M (2012) Interregionale en grensoverschrijdende mobiliteit in België . Een analyse op basis van de Vlaamse WSE-Report Interregionale en grensoverschrijdende mobiliteit in België . Een analyse op basis van de Vlaamse Arbeidsrekening. Steunpunt WSE, KU LeuvenGoogle Scholar
  51. Vandersmissen M-H, Thomas I, Verhetsel A (2011) Commuting and gender: two cities, one reality? In Modeling urban dynamics/ Thériault, Marius et al (pp. 27–55). WileyGoogle Scholar
  52. Verhetsel A, Thomas I, Van Hecke E, Beelen M (2007) Algemene sociaal-economische enquête 2001, monografie pendel in België in 2001: Deel 1: de woon-werkverplaatsingen. Federaal Wetenschapsbeleid En FOD Economie-Algemene Directie Statistiek, BrusselGoogle Scholar
  53. Verhetsel A, Vanelslander T (2010) What location policy can bring to sustainable commuting: an empirical study in Brussels and Flanders, Belgium. J Transp Geogr 18(6):691–701.  https://doi.org/10.1016/j.jtrangeo.2009.11.003 CrossRefGoogle Scholar
  54. Vliegen M (2005) Grootstedelijke agglomeraties en stadsgewesten afgebakend Google Scholar
  55. Wasseige YDE, Laffut M, Ruyters C, Schleiper P (2001) Bassins d’emploi et regions fonctionnelles - methodologie et definition des bassins d’emplois Belges. Ministère de la Région wallonne, Service des Etudes de la StatistiqueGoogle Scholar
  56. Williams B, Walsh C, Boyle I (2010) The development of the functional urban region of Dublin: Implications for regional development markets and planning. Journal of Irish Urban Studies 7(9):5–30Google Scholar
  57. Zhao P (2015) The determinants of the commuting burden of low-income workers: Evidence from Beijing. Environ Plan A 47:1736–1755.  https://doi.org/10.1177/0308518X15597112 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Transport and Regional EconomicsUniversity of AntwerpAntwerpenBelgium

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