Skip to main content
SpringerLink
Log in

Daily Spatial Footprint of Warsaw Metropolitan Area (Poland) Commuters in Light of Volunteered Geographic Information and Common Factors of Urban Sprawl. A Pilot Study

  • Conference paper
  • First Online:
Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12252))

Included in the following conference series:

Abstract

Urban sprawl directly affects on length of commuting. Acquisition of commuting data is based on theoretical (deductive) approaches, limited individual small observation samples or indirect phenomena like e.g. remote sensing night light data images. Volunteered Geographic Information (VGI) make possible deeper insight into the daily spatial footprint of commuting and is related to urban sprawl. Data acquired during the collection of VGI data reveal some new aspects of spatial phenomena, which can be additionally analyzed. VGI data concerning spatial phenomena involve both geotagging as well time stamps of acquisition, which in turn make possible indirectly inferring about spatial and temporal move of people. Analysis of the available spatial and temporal VGI data in context of national surveying acquired resources (INSPIRE) and confronted to modelling approach of commuting is the subject of pilot study of Warsaw functional urban area. The results are promising due to inter alia, generalization of huge volume real data observations set unlike to formerly used theoretical modelling.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Hasse, J.E., Lathrop, R.G.: Land resource impact indicators of urban sprawl. Appl. Geogr. 23, 159–175 (2003). https://doi.org/10.1016/j.apgeog.2003.08.002

    Article  Google Scholar 

  2. Jaeger, J.A.G., Bertiller, R., Schwick, C., Kienast, F.: Suitability criteria for measures of urban sprawl. Ecol. Ind. 10, 397–406 (2010). https://doi.org/10.1016/j.ecolind.2009.07.007

    Article  Google Scholar 

  3. Haas, A., Osland, L.: Commuting, Migration, Housing and Labour Markets: Complex Interactions. Urban Stud. 51, 463–476 (2014). https://doi.org/10.1177/0042098013498285

    Article  Google Scholar 

  4. Guastella, G., Oueslati, W., Pareglio, S.: Patterns of urban spatial expansion in European cities. Sustainability 11, 2247 (2019). https://doi.org/10.3390/su11082247

    Article  Google Scholar 

  5. Wu, J.: Environmental amenities, urban sprawl, and community characteristics. J. Environ. Econ. Manage. 52, 527–547 (2006). https://doi.org/10.1016/j.jeem.2006.03.003

    Article  MATH  Google Scholar 

  6. Handy, S.: Smart growth and the transportation-land use connection: what does the research tell us? Int. Reg. Sci. Rev. 28, 146–167 (2005). https://doi.org/10.1177/0160017604273626

    Article  Google Scholar 

  7. Sultana, S., Weber, J.: The nature of urban growth and the commuting transition: endless sprawl or a growth wave? Urban Stud. 51, 544–576 (2014). https://doi.org/10.1177/0042098013498284

    Article  Google Scholar 

  8. Vanderhaegen, S., Canters, F.: Mapping urban form and function at city block level using spatial metrics. Landscape Urban Planning 167, 399–409 (2017). https://doi.org/10.1016/j.landurbplan.2017.05.023

    Article  Google Scholar 

  9. Herold, M., Scepan, J., Clarke, K.C.: The use of remote sensing and landscape metrics to describe structures and changes in urban land uses. Environ. Plan. A. 34, 1443–1458 (2002). https://doi.org/10.1068/a3496

    Article  Google Scholar 

  10. Elwood, S., Goodchild, M.F., Sui, D.Z.: Researching volunteered geographic information: spatial data, geographic research, and new social practice. Ann. Assoc. Am. Geogr. 102, 571–590 (2012). https://doi.org/10.1080/00045608.2011.595657

    Article  Google Scholar 

  11. Senaratne, H., Mobasheri, A., Ali, A.L., Capineri, C., Haklay, M.: (Muki): A review of volunteered geographic information quality assessment methods. Int. J. Geogr. Inf. Sci. 31, 139–167 (2017). https://doi.org/10.1080/13658816.2016.1189556

    Article  Google Scholar 

  12. Montello, D.R., Goodchild, M.F., Gottsegen, J., Fohl, P.: Where’s downtown?: behavioral methods for determining referents of vague spatial queries. Spatial Cogn. Comput. 3, 185–204 (2003). https://doi.org/10.1080/13875868.2003.9683761

    Article  Google Scholar 

  13. Hollenstein, L., Purves, R.: Exploring place through user-generated content: Using Flickr to describe city cores. JOSIS, 21–48 (2010). https://doi.org/10.5311/JOSIS.2010.1.3

  14. See, L., et al.: Crowdsourcing, citizen science or volunteered geographic information? the current state of crowdsourced geographic information. IJGI 5, 55 (2016). https://doi.org/10.3390/ijgi5050055

    Article  Google Scholar 

  15. Bishr, M., Janowicz, K.: Can we trust information? - the case of volunteered geographic information. In: Towards Digital Earth Search Discover and Share Geospatial Data Workshop at Future Internet Symposium, vol. 640. CEUR-WS (2010)

    Google Scholar 

  16. Minghini, M., Kotsev, A., Lutz, M.: Comparing INSPIRE and Open Street Map data: how to make the most out of the two worlds. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. XLII-4/W14, 167–174 (2019). https://doi.org/10.5194/isprs-archives-XLII-4-W14-167-2019

  17. Capineri, C., Haklay, M., Huang, H., Kettunen, J., Ostermann, F., Purves, R. (eds.): European Handbook of Crowdsourced Geographic Information. Ubiquity Press (2016). https://doi.org/10.5334/bax

  18. OpenCelliD - Largest Open Database of Cell Towers & Geolocation - by Unwired Labs. http://www.opencellid.org. Accessed 02 Jan 2019

  19. Ricciato, F., Widhalm, P., Craglia, M., Pantisano, F.: Estimating population density distribution from network-based mobile phone data. Publications Office of the European Union (2015)

    Google Scholar 

  20. Werner, P.A., Porczek, M.: Spatial patterns of development of mobile technologies for 5G networks. In: Misra, S., et al. (eds.) ICCSA 2019. LNCS, vol. 11621, pp. 448–459. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-24302-9_32

    Chapter  Google Scholar 

  21. Florczyk, A.J., et al.: European Commission, Joint Research Centre: GHSL data package 2019: public release GHS P2019 (2019)

    Google Scholar 

  22. Geoportal.gov.pl. http://geoportal.gov.pl. Accessed 26 Feb 2020

  23. Warsaw (2020). https://en.wikipedia.org/w/index.php?title=Warsaw&oldid=962362880

  24. Statistics Poland. https://stat.gov.pl/en/. Accessed 13 June 2020

  25. Korcelli, P., Grochowski, M., Kozubek, E., Korcelli-Olejniczak, E., Werner, P.: Development of urban-rural regions: from European to local perspective. IGiPZ PAN, Warszawa (2013)

    Google Scholar 

  26. Glossary: Urban cluster - Statistics Explained. https://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:Urban_cluster. Accessed 14 Mar 2020

  27. Golden Software, Inc.: Surfer. Contouring and 3D Surface Mapping for Scientists and Engineers. Golden Software, Inc. (2003)

    Google Scholar 

  28. Werner, P.: Simulation of changes of the Warsaw Urban Area 1969-2023 (Application of Cellular Automata), Miscellanea Geographica. 329–335 (2006). https://doi.org/10.2478/mgrsd-2006-0037

Download references

Author information

Authors and Affiliations

  1. Institute of Urban and Regional Development, Targowa 45, 03-782, Warsaw, Poland

    Veranika Kaleyeva

  2. Faculty of Geography and Regional Studies, University of Warsaw, Krak. Przedm. 30, 00-927, Warsaw, Poland

    Piotr A. Werner

Authors
  1. Veranika Kaleyeva
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Piotr A. Werner
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Piotr A. Werner .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Chair- Center of ICT/ICE, Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Clayton School of Information Technology, Monash University, Clayton, VIC, Australia

    David Taniar

  7. Department of Information Science, Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

  11. Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA

    Yeliz Karaca

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kaleyeva, V., Werner, P.A. (2020). Daily Spatial Footprint of Warsaw Metropolitan Area (Poland) Commuters in Light of Volunteered Geographic Information and Common Factors of Urban Sprawl. A Pilot Study. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12252. Springer, Cham. https://doi.org/10.1007/978-3-030-58811-3_26

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-58811-3_26

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58810-6

  • Online ISBN: 978-3-030-58811-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation