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Comparison of Simulated Fast and Green Routes for Cyclists and Pedestrians

Authors Christina Ludwig , Sven Lautenbach , Eva-Marie Schömann, Alexander Zipf

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Author Details

Christina Ludwig
  • GIScience Research Group, Institute of Geography, Heidelberg University, Germany
Sven Lautenbach
  • Heidelberg Institute for Geoinformation Technology (HeiGIT) gGmbH at Heidelberg University, Germany
Eva-Marie Schömann
  • GIScience Research Group, Institute of Geography, Heidelberg University, Germany
Alexander Zipf
  • GIScience Research Group, Institute of Geography, Heidelberg University, Germany
  • HeiGIT gGmbH at Heidelberg University, Germany

Funding

This research was funded by the German Federal Ministry of Transport and Digital Infrastructure (BMVI) in the context of the research initiative mFUND (grant number 19F2073A).
  • Lautenbach, Sven: Acknowledges funding by the Klaus-Tschira Stiftung.

Acknowledgements

We would like to thank several research assistants involved in the project, namely Anna Lausen, Pascal Wolf as well as Robert Klar and Max Girmann who wrote their theses in the context of healthy routing. We acknowledge support by the HeiGIT openrouteservice team, especially by Adam Rousell and Andrzej Oleś as well as by the HeiGIT big spatial data team. Furthermore, we would like to thank the meinGrün project team (http://meingruen.ioer.info/) for fruitful discussions and the city administration of Dresden and Heidelberg for their support.

Cite As Get BibTex

Christina Ludwig, Sven Lautenbach, Eva-Marie Schömann, and Alexander Zipf. Comparison of Simulated Fast and Green Routes for Cyclists and Pedestrians. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 3:1-3:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/LIPIcs.GIScience.2021.II.3

Abstract

Routes with a high share of greenery are attractive for cyclist and pedestrians. We analyze how strongly such green routes differ from the respective fast routes using the openrouteservice. Greenness of streets was estimated based on OpenStreetMap data in combination with Sentinel-II imagery, 3d laser scan data and administrative information on trees on public ground. We assess the effect both at the level of the individual route and at the urban level for two German cities: Dresden and Heidelberg. For individual routes, we study how strongly green routes differ from the respective fast routes. In addition, we identify parts of the road network which represent important green corridors as well as unattractive parts which can or cannot be avoided at the cost of reasonable detours. In both cities, our results show the importance of urban green spaces for the provision of attractive green routes and provide new insights for urban planning by identifying unvegetated bottlenecks in the street network for which no green alternatives exist at this point.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Simulation evaluation
  • General and reference → Empirical studies
  • Applied computing → Cartography
Keywords
  • Routing
  • OpenStreetMap
  • route choice
  • urban vegetation
  • sustainable mobility

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References

  1. Sabreena Anowar, Naveen Eluru, and Marianne Hatzopoulou. Quantifying the value of a clean ride: How far would you bicycle to avoid exposure to traffic-related air pollution? Transportation Research Part A: Policy and Practice, 105:66-78, 2017. URL: https://doi.org/10.1016/j.tra.2017.08.017.
  2. Christopher Barron, Pascal Neis, and Alexander Zipf. A Comprehensive Framework for Intrinsic OpenStreetMap Quality Analysis. Transactions in GIS, 18(6):877-895, 2014. URL: https://doi.org/10.1111/tgis.12073.
  3. Scott Chamberlain and Andy Teucher. geojsonio: Convert Data from and to 'GeoJSON' or 'TopoJSON', 2021. R package version 0.9.4. URL: https://CRAN.R-project.org/package=geojsonio.
  4. Lívia Castro Degrossi, João Porto de Albuquerque, Roberto dos Santos Rocha, and ALexander Zipf. A Framework of Quality Assessment Methods for Crowdsourced Geographic Information: a Systematic Literature Review. In Proceedings of the 14th ISCRAM Conference, pages 21-24, 2017. Issue: May. Google Scholar
  5. Dawn C Dickinson and Richard J Hobbs. Cultural ecosystem services: Characteristics, challenges and lessons for urban green space research. Ecosystem Services, 25:179-194, 2017. Google Scholar
  6. E W Dijkstra. A note on two problems in connexion with graphs. Numerische Mathematik, 1:269-271, 1959. Google Scholar
  7. German Aerospace Center (DLR). Land Cover DE - Sentinel-2 - Germany, 2015, 2020. URL: https://doi.org/10.15489/1ccmlap3mn39.
  8. Erik Gómez-Baggethun, Åsa Gren, David N Barton, Johannes Langemeyer, Timon McPhearson, Patrick O’farrell, Erik Andersson, Zoé Hamstead, and Peleg Kremer. Urban ecosystem services. In Urbanization, biodiversity and ecosystem services: Challenges and opportunities, pages 175-251. Springer, Dordrecht, 2013. URL: https://doi.org/10.1007/978-94-007-7088-1.
  9. P. Grubitzsch, S. Lißner, S. Huber, and T. Springer, 2021. Accessed: 23.4.2021. URL: https://www.mcloud.de/web/guest/suche/-/results/suche/relevance/MOVEBIS/0/detail/ECF9DF02-37DC-4268-B017-A7C2CF302006.
  10. Peter E. Hart, Nils J. Nillson, and Bertram Raphael. A Formal Basis for the Heuristic Determination of Minimum Cost Paths. IEEE transactions on Systems Science and Cybernetics, 4(2):100-107, 1968. URL: https://www.cs.auckland.ac.nz/compsci767s2c/projectReportExamples.d/astarNilsson.pdf.
  11. Robert Hecht, Gotthard Meinel, and Manfred F Buchroithner. Estimation of urban green volume based on single-pulse lidar data. IEEE Transactions on Geoscience and Remote Sensing, 46(11):3832-3840, 2008. URL: https://doi.org/10.1109/TGRS.2008.2001771.
  12. Victoria Houlden, Scott Weich, João Porto de Albuquerque, Stephen Jarvis, and Karen Rees. The relationship between greenspace and the mental wellbeing of adults: A systematic review. PLOS ONE, 13(9):e0203000, September 2018. URL: https://doi.org/10.1371/journal.pone.0203000.
  13. Isaac Johnson, Jessica Henderson, Caitlin Perry, Johannes Schöning, and Brent Hecht. Beautiful… but at what cost? an examination of externalities in geographic vehicle routing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 1(2):1-21, 2017. URL: https://doi.org/10.1145/3090080.
  14. Alboukadel Kassambara. ggpubr: 'ggplot2' Based Publication Ready Plots, 2020. R package version 0.4.0. URL: https://CRAN.R-project.org/package=ggpubr.
  15. Michelle Kondo, Jaime Fluehr, Thomas McKeon, and Charles Branas. Urban green space and its impact on human health. International Journal of Environmental Research and Public Health, 15(3):445, 2018. URL: https://doi.org/10.3390/ijerph15030445.
  16. Kerstin Krellenberg, Juliane Welz, and Sonia Reyes-Päcke. Urban green areas and their potential for social interaction-a case study of a socio-economically mixed neighbourhood in Santiago de Chile. Habitat International, 44:11-21, 2014. Google Scholar
  17. Anna Lausen. Analyse der Verwendbarkeit von OSM Daten für ein grünes Routing am Beispiel Dresden. Bachelor’s thesis, Heidelberg University, Institute of Geography, Heidelberg, Germany, January 2020. Google Scholar
  18. Claudia Lega, Christopher Gidlow, Marc Jones, Naomi Ellis, and Gemma Hurst. The relationship between surrounding greenness, stress and memory. Urban Forestry & Urban Greening, 59:126974, 2021. URL: https://doi.org/10.1016/j.ufug.2020.126974.
  19. Christina Ludwig, Robert Hecht, Sven Lautenbach, Martin Schorcht, and Alexander Zipf. Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions. ISPRS International Journal of Geo-Information, 10(4):251, April 2021. URL: https://doi.org/10.3390/ijgi10040251.
  20. J. Maas. Green space, urbanity, and health: how strong is the relation? Journal of Epidemiology & Community Health, 60(7):587-592, July 2006. URL: https://doi.org/10.1136/jech.2005.043125.
  21. David Philip McArthur and Jinhyun Hong. Visualising where commuting cyclists travel using crowdsourced data. Journal of transport geography, 74:233-241, 2019. URL: https://doi.org/10.1016/j.jtrangeo.2018.11.018.
  22. Pascal Neis and Alexander Zipf. Openrouteservice.org is three times “open”: Combining OpenSource, OpenLS and OpenStreetMaps. In GIS Research UK (GISRUK 08). Manchester, 2008. Google Scholar
  23. Tessio Novack, Zhiyong Wang, and Alexander Zipf. A system for generating customized pleasant pedestrian routes based on openstreetmap data. Sensors, 18(11):3794, 2018. Google Scholar
  24. Yujin Park and Gulsah Akar. Why do bicyclists take detours? a multilevel regression model using smartphone gps data. Journal of transport geography, 74:191-200, 2019. Google Scholar
  25. Edzer Pebesma. Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal, 10(1):439-446, 2018. URL: https://doi.org/10.32614/RJ-2018-009.
  26. Andrea Pimpinella, Alessandro E.C. Redondi, and Matteo Cesana. Walk this way! an IoT-based urban routing system for smart cities. Computer Networks, 162:106857, 2019. URL: https://doi.org/10.1016/j.comnet.2019.07.013.
  27. R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, 2021. URL: https://www.R-project.org/.
  28. Martin Raifer, Rafael Troilo, Fabian Kowatsch, Michael Auer, Lukas Loos, Sabrina Marx, Katharina Przybill, Sascha Fendrich, Franz-Benjamin Mocnik, and Alexander Zipf. OSHDB: a framework for spatio-temporal analysis of OpenStreetMap history data. Open Geospatial Data, Software and Standards, 4(1), 2019. URL: https://doi.org/10.1186/s40965-019-0061-3.
  29. Karl Rehrl, Stefan Kranzinger, and Simon Gröchenig. Which quality is a route? a methodology for assessing route quality using spatio-temporal metrics. Transactions in GIS, 25(2):869-896, 2021. URL: https://doi.org/10.1111/tgis.12705.
  30. Daniel A. Rodríguez, Louis Merlin, Carlo G. Prato, Terry L. Conway, Deborah Cohen, John P. Elder, Kelly R. Evenson, Thomas L. McKenzie, Julie L. Pickrel, and Sara Veblen-Mortenson. Influence of the built environment on pedestrian route choices of adolescent girls. Environment and Behavior, 47(4):359-394, 2015. URL: https://doi.org/10.1177/0013916513520004.
  31. Sophie Schetke, Salman Qureshi, Sven Lautenbach, and Nadja Kabisch. What determines the use of urban green spaces in highly urbanized areas? – Examples from two fast growing Asian cities. Urban Forestry & Urban Greening, 16:150-159, 2016. URL: https://doi.org/10.1016/j.ufug.2016.02.009.
  32. Hansi Senaratne, Amin Mobasheri, Ahmed Loai Ali, Cristina Capineri, and Mordechai (Muki) Haklay. A review of volunteered geographic information quality assessment methods. International Journal of Geographical Information Science, 31(1):139-167, 2017. URL: https://doi.org/10.1080/13658816.2016.1189556.
  33. P. N. Seneviratne and J. F. Morrall. Analysis of factors affecting the choice of route of pedestrians. Transportation Planning and Technology, 10(2):147-159, 1985. URL: https://doi.org/10.1080/03081068508717309.
  34. Monir H. Sharker and Hassan A. Karimi. Computing least air pollution exposure routes. International Journal of Geographical Information Science, 28(2):343-362, 2014. URL: https://doi.org/10.1080/13658816.2013.841317.
  35. P. Siriaraya, Y. Wang, Y. Zhang, S. Wakamiya, P. Jeszenszky, Y. Kawai, and A. Jatowt. Beyond the shortest route: A survey on quality-aware route navigation for pedestrians. IEEE Access, 8:135569-135590, 2020. Conference Name: IEEE Access. URL: https://doi.org/10.1109/ACCESS.2020.3011924.
  36. Duncan Temple Lang. RCurl: General Network (HTTP/FTP/...) Client Interface for R, 2021. R package version 1.98-1.3. URL: https://CRAN.R-project.org/package=RCurl.
  37. Heike Tost, Markus Reichert, Urs Braun, Iris Reinhard, Robin Peters, Sven Lautenbach, Andreas Hoell, Emanuel Schwarz, Ulrich Ebner-Priemer, Alexander Zipf, and Andreas Meyer-Lindenberg. Neural correlates of individual differences in affective benefit of real-life urban green space exposure. Nature Neuroscience, 2019. URL: https://doi.org/10.1038/s41593-019-0451-y.
  38. Asha Weinstein Agrawal, Marc Schlossberg, and Katja Irvin. How far, by which route and why? a spatial analysis of pedestrian preference. Journal of Urban Design, 13(1):81-98, 2008. URL: https://doi.org/10.1080/13574800701804074.
  39. Hadley Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016. URL: https://ggplot2.tidyverse.org.
  40. Hadley Wickham, Mara Averick, Jennifer Bryan, Winston Chang, Lucy D'Agostino McGowan, Romain François, Garrett Grolemund, Alex Hayes, Lionel Henry, Jim Hester, Max Kuhn, Thomas Lin Pedersen, Evan Miller, Stephan Milton Bache, Kirill Müller, Jeroen Ooms, David Robinson, Dana Paige Seidel, Vitalie Spinu, Kohske Takahashi, Davis Vaughan, Claus Wilke, Kara Woo, and Hiroaki Yutani. Welcome to the tidyverse. Journal of Open Source Software, 4(43):1686, 2019. URL: https://doi.org/10.21105/joss.01686.
  41. Bin Zou, Shenxin Li, Zhong Zheng, Benjamin F. Zhan, Zhonglin Yang, and Neng Wan. Healthier routes planning: A new method and online implementation for minimizing air pollution exposure risk. Computers, Environment and Urban Systems, 80:101456, 2020. URL: https://doi.org/10.1016/j.compenvurbsys.2019.101456.
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