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OpenStreetMap in GIScience pp 229–251Cite as

Building a Multimodal Urban Network Model Using OpenStreetMap Data for the Analysis of Sustainable Accessibility

Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

This chapter presents the process of building a multimodal urban network model using Volunteered Geographic Information (VGI) and in particular OpenStreetMap (OSM). The spatial data model design adopts a level of simplification that is adequate to OSM data availability and quality, and suitable to the measurement of the sustainable accessibility of urban neighborhoods and city-regions. The urban network model connects a private transport system (i.e. pedestrian, bicycle, car), a public transport system (i.e. rail, metro, tram and bus) and a land use system (i.e. building land use units). Various algorithmic procedures have been developed to produce the network model, supporting the reproducibility of the process and addressing the challenges of using OSM data for this purpose. While OSM demonstrates great potential for urban analysis, thanks to the detail of its attributes and its open and universal coverage, there is still some way to go to provide the data quality and consistency required for detailed operational urban models.

Keywords

  • Multimodal networks
  • Street networks
  • Network model
  • Spatial network analysis
  • Sustainable accessibility

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Notes

  1. 1.

    For details refer to the maps on http://wiki.openstreetmap.org/wiki/WikiProject_Netherlands.

  2. 2.

    http://www.openov.nl/.

  3. 3.

    http://bag.vrom.nl/.

References

  • Ayed H, Galvez-Fernandez C, Habbas Z, Khadraoui D (2011) Solving time-dependent multimodal transport problems using a transfer graph model. Comput Ind Eng 61:391–401. doi:10.1016/j.cie.2010.05.018

    CrossRef  Google Scholar 

  • Ballester MG, Pérez MR, Stuiver J (2011) Automatic pedestrian network generation. pp 1–13

    Google Scholar 

  • Bertolini L, le Clercq F, Kapoen L (2005) Sustainable accessibility: a conceptual framework to integrate transport and land use plan-making. Two test-applications in the Netherlands and a reflection on the way forward. Transp Policy 12:207–220. doi:10.1016/j.tranpol.2005.01.006

    CrossRef  Google Scholar 

  • Bielli M, Boulmakoul A, Mouncif H (2006) Object modeling and path computation for multimodal travel systems. Eur J Oper Res 175:1705–1730. doi:10.1016/j.ejor.2005.02.036

    CrossRef  Google Scholar 

  • Butler JA, Dueker KJ (2001) Implementing the enterprise GIS in transportation database design. J Urban Reg Inf Syst Assoc 13:17

    Google Scholar 

  • Chen S, Tan J, Claramunt C, Ray C (2011) Multi-scale and multi-modal GIS-T data model. J Transp Geogr 19:147–161. doi:10.1016/j.jtrangeo.2009.09.006

    CrossRef  Google Scholar 

  • Chin GKW, Van Niel KP, Giles-Corti B, Knuiman M (2008) Accessibility and connectivity in physical activity studies: The impact of missing pedestrian data. Prev Med 46:41–45. doi:10.1016/j.ypmed.2007.08.004

    CrossRef  Google Scholar 

  • Estima J, Painho M (2013) Exploratory analysis of OpenStreetMap for land use classification. In: Proceedings of the second ACM SIGSPATIAL international workshop on crowdsourced and volunteered geographic information, pp. 39–46. ACM, New York. doi:10.1145/2534732.2534734

  • Fonseca FT, Egenhofer MJ, Davis CA, Borges KAV (2000) Ontologies and knowledge sharing in urban GIS. Comput Environ Urban Syst 24:251–272. doi:10.1016/S0198-9715(00)00004-1

    CrossRef  Google Scholar 

  • Friedrich M (1998) A multi-modal transport model for integrated planning. In: World conference on transport research society, pp 1–14. Antwerpen

    Google Scholar 

  • Galvez-Fernandez C, Khadraoui D, Ayed H et al (2009) Distributed approach for solving time-dependent problems in multimodal transport networks. Adv Oper Res 2009:e512613. doi:10.1155/2009/512613

    Google Scholar 

  • Gil J (2014) Analyzing the configuration of multi-modal urban networks. Geogr Anal 46:368–391. doi:10.1111/gean.12062

    Google Scholar 

  • Gil J, Read S (2012) Measuring sustainable accessibility potential using the mobility infrastructure’s network configuration. In: Proceedings: 8th international space syntax symposium, pp 8104:1–8104:19. Pontificia Universidad Catolica de Chile, Santiago

    Google Scholar 

  • Gil J, Read S (2014) Patterns of sustainable mobility and the structure of modality in the Randstad city-region. A|Z ITU J Fac Architect 11

    Google Scholar 

  • Girres J-F, Touya G (2010) Quality assessment of the French OpenStreetMap dataset. Trans GIS 14:435–459. doi:10.1111/j.1467-9671.2010.01203.x

    CrossRef  Google Scholar 

  • Goodchild MF (2000) GIS and transportation: status and challenges. GeoInformatica 4:127–139–139

    Google Scholar 

  • Goodchild MF, Li L (2012) Assuring the quality of volunteered geographic information. Spat Stat 1:110–120. doi:10.1016/j.spasta.2012.03.002

    CrossRef  Google Scholar 

  • Graser A, Straub M, Dragaschnig M (2014) Towards an open source analysis toolbox for street network comparison: indicators, tools and results of a comparison of OSM and the official Austrian reference graph. Trans GIS 18:510–526. doi:10.1111/tgis.12061

    CrossRef  Google Scholar 

  • Hadas Y (2013) Assessing public transport systems connectivity based on Google Transit data. J Transp Geogr 33:105–116. doi:10.1016/j.jtrangeo.2013.09.015

    CrossRef  Google Scholar 

  • Haklay M (2010) How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets. Environ Plan 37:682–703. doi:10.1068/b35097

    CrossRef  Google Scholar 

  • Haklay M, Weber P (2008) OpenStreetMap: user-generated street maps. IEEE Pervasive Comput 7:12–18. doi:10.1109/MPRV.2008.80

    CrossRef  Google Scholar 

  • Ismail MA, Said MN (2014) Integration of geospatial multi-mode transportation systems in Kuala Lumpur. IOP Conf Ser: Earth Environ Sci 20:012–027. doi:10.1088/1755-1315/20/1/012027

    Google Scholar 

  • Jiang B (2011) A Short Note on Data-Intensive Geospatial Computing. In: Popovich VV, Claramunt C, Devogele T et al (eds) Information fusion and geographic information systems. Springer, Berlin, pp 13–17

    CrossRef  Google Scholar 

  • Jiang B (2013) Volunteered geographic information and computational geography: new perspectives. In: Sui D, Elwood S, Goodchild M (eds) Crowdsourcing geographic knowledge. Springer, Netherlands, pp 125–138

    CrossRef  Google Scholar 

  • Jokar Arsanjani J, Vaz E (2015) An assessment of a collaborative mapping approach for exploring land use patterns for several European metropolises. Int J Appl Earth Obs Geoinf (in press)

    Google Scholar 

  • Jokar Arsanjani J, Barron C, Bakillah M, Helbich M (2013a) Assessing the quality of OpenStreetMap contributors together with their contributions. In: 16th AGILE international conference on geographic information science, Leuven, Belgium. 14–17 May 2013

    Google Scholar 

  • Jokar Arsanjani J, Helbich M, Bakillah M et al. (2013b) Toward mapping land-use patterns from volunteered geographic information. Int J Geogr Inf Sci 27:2264–2278. doi:10.1080/13658816.2013.800871

  • Karimi HA, Kasemsuppakorn P (2012) Pedestrian network map generation approaches and recommendation. Int J Geogr Inf Sci 27:947–962. doi:10.1080/13658816.2012.730148

  • Kim J, yong Park S, Bang Y, Yu K (2009) Automatic derivation of a pedestrian network based on existing spatial data sets

    Google Scholar 

  • Le Clercq F, Bertolini L (2003) Achieving sustainable accessibility: an evaluation of policy measures in the Amsterdam area. Built Environ 29:36–47. doi:10.2148/benv.29.1.36.53949

    CrossRef  Google Scholar 

  • Li Z-C, Huang H-J, Lam WHK, Wong SC (2007) A Model for evaluation of transport policies in multimodal networks with road and parking capacity constraints. J Math Model Algor 6:239–257. doi:10.1007/s10852-006-9040-7

    CrossRef  Google Scholar 

  • Liu L (2011) Data model and algorithms for multimodal route planning with transportation networks. Technische Universität München, PhD

    Google Scholar 

  • Lozano A, Storchi G (2001) Shortest viable path algorithm in multimodal networks. Transp Res Part A Policy Pract 35:225–241. doi:10.1016/S0965-8564(99)00056-7

    CrossRef  Google Scholar 

  • Mavoa S, Witten K, McCreanor T, O’Sullivan D (2012) GIS based destination accessibility via public transit and walking in Auckland, New Zealand. J Transp Geogr 20:15–22. doi:10.1016/j.jtrangeo.2011.10.001

    CrossRef  Google Scholar 

  • Miller HJ, Shaw S-L (2001) Geographic information systems for transportation: principles and applications. Oxford University Press, Oxford

    Google Scholar 

  • Mooney P, Corcoran P, Winstanley AC (2010) Towards Quality Metrics for OpenStreetMap. Proceedings of the 18th SIGSPATIAL international conference on advances in geographic information systems, pp 514–517. ACM, New York

    Google Scholar 

  • Mouncif H, Boulmakoul A, Chala M (2006) Integrating GIS-Technology for Modelling Origin-Destination Trip in Multimodal Transportation Networks. Int Arab J Inf Technol 3:256–264

    Google Scholar 

  • Neis P, Zielstra D (2014) Generation of a tailored routing network for disabled people based on collaboratively collected geodata. Appl Geogr 47:70–77. doi:10.1016/j.apgeog.2013.12.004

    CrossRef  Google Scholar 

  • Neis P, Zielstra D, Zipf A (2011) The street network evolution of crowdsourced maps: OpenStreetMap in Germany 2007–2011. Future Internet 4:1–21. doi:10.3390/fi4010001

    CrossRef  Google Scholar 

  • Scheider S, Kuhn W (2010) Affordance-based categorization of road network data using a grounded theory of channel networks. Int J Geogr Inf Sci 24:1249–1267. doi:10.1080/13658810903514198

    CrossRef  Google Scholar 

  • Scheurer J, Curtis C (2008) Spatial network analysis of multimodal transport systems: developing a strategic planning tool to assess the congruence of movement and urban structure. Curtin University of Technology, Perth

    Google Scholar 

  • Scioscia F, Binetti M, Ruta M et al (2014) A framework and a tool for semantic annotation of POIs in OpenStreetMap. Procedia—Soc Behav Sci 111:1092–1101. doi:10.1016/j.sbspro.2014.01.144

    CrossRef  Google Scholar 

  • Sester M, Jokar Arsanjani J, Klammer R et al. (2014) Integrating and generalising volunteered geographic information. In: Burghardt D, Duchêne C, Mackaness W (eds) Abstracting geographic information in a data rich world. Springer International Publishing, New York, pp 119–155

    Google Scholar 

  • Stead D, Marshall S (2001) The relationships between urban form and travel patterns. Int Rev Evaluat EJTIR 1:113–141

    Google Scholar 

  • Van Nes R (2002) Design of multimodal transport networks. PhD, Civil Engineering, Delft Technical University

    Google Scholar 

  • Van Wee B (2002) Land use and transport: research and policy challenges. J Transp Geogr 10:259–271. doi:10.1016/S0966-6923(02)00041-8

    CrossRef  Google Scholar 

  • Yigitcanlar T, Sipe N, Evans R, Pitot M (2007) A GIS-based land use and public transport accessibility indexing model. Aust Plan 44:30–37. doi:10.1080/07293682.2007.9982586

    CrossRef  Google Scholar 

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Acknowledgments

This research was generously funded by the Fundação para a Ciência e Tecnologia (FCT)—Portuguese Science and Technology Foundation—with grant SFRH/BD/46709/2008.

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Authors and Affiliations

  1. Faculty of Architecture, Department of Urbanism, Delft University of Technology, Julianalaan 134, 2628 BL, Delft, The Netherlands

    Jorge Gil

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  1. Jorge Gil
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Correspondence to Jorge Gil .

Editor information

Editors and Affiliations

  1. GIScience research group, Institute of Geography, Heidelberg, Germany

    Jamal Jokar Arsanjani

  2. Geography, Institute of Geography, Heidelberg, Germany

    Alexander Zipf

  3. Department of Computer Science, Maynooth University, Maynooth Co Kildare, Kildare, Ireland

    Peter Mooney

  4. Department of Human Geography and Spatial Planning, Faculty of Geosciences, Utrecht, The Netherlands

    Marco Helbich

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Gil, J. (2015). Building a Multimodal Urban Network Model Using OpenStreetMap Data for the Analysis of Sustainable Accessibility. In: Jokar Arsanjani, J., Zipf, A., Mooney, P., Helbich, M. (eds) OpenStreetMap in GIScience. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-14280-7_12

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