IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i11p4631-d1404964.html

Extraction of Geolocations from Site Maps in the Context of Traffic Counting

Author

Listed:
  • Johannes Schering

    (Department of Business Informatics VLBA, University of Oldenburg, Ammerländer Heerstr. 114-118, 26129 Oldenburg, Germany)

  • Pascal Säfken

    (Department of Business Informatics VLBA, University of Oldenburg, Ammerländer Heerstr. 114-118, 26129 Oldenburg, Germany)

  • Jorge Marx Gómez

    (Department of Business Informatics VLBA, University of Oldenburg, Ammerländer Heerstr. 114-118, 26129 Oldenburg, Germany)

Abstract

The further promotion of cycling is a key component for each city to reach its sustainability goals. To make decisions to improve comfort or safety for cyclists, the amount of motorized traffic should be taken into account. Therefore, traffic data play a crucial role not only in the construction of roads but also in cycling planning. This data source provides insights essential for road infrastructure development and optimizing various modes of transportation, such as bike paths. However, processing municipal traffic data becomes a challenge when stationary traffic-counting stations lack geo-referencing in relational databases. In this case, the locations of traffic counters are solely displayed on a PDF-based site map without inherent geo-referencing, and the geo-coordinates are not stored in any relational database. The absence of geo-references poses a significant hurdle for traffic-planning experts in decision-making processes. Hence, this study aims to address this issue by finding a suitable approach to extract the geo-coordinates from the site maps. Several potential solutions are discussed and compared in terms of time dimension, usability, extensibility, error treatment and the accuracy of results. Leveraging the open-source tool QGIS, geo-coordinates may be successfully extracted from the PDF-based site maps, resulting in the creation of a GeoTIFF file incorporating coordinates and the rotated site map. Geo-coordinates can then be derived from the GeoTIFF files using x and y coordinates, computed through the rotation matrix formula. Over 1400 measurement locations may be extracted based on the preferred approach, facilitating more informed decision-making in traffic planning.

Suggested Citation

  • Johannes Schering & Pascal Säfken & Jorge Marx Gómez, 2024. "Extraction of Geolocations from Site Maps in the Context of Traffic Counting," Sustainability, MDPI, vol. 16(11), pages 1-14, May.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:11:p:4631-:d:1404964
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/11/4631/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/11/4631/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Morteza Hossein Sabbaghian & David Llopis-Castelló & Alfredo García, 2023. "A Safe Infrastructure for Micromobility: The Current State of Knowledge," Sustainability, MDPI, vol. 15(13), pages 1-20, June.
    2. Stanley, John K. & Hensher, David A. & Loader, Chris, 2011. "Road transport and climate change: Stepping off the greenhouse gas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(10), pages 1020-1030.
    3. Ralph Buehler & Jennifer Dill, 2016. "Bikeway Networks: A Review of Effects on Cycling," Transport Reviews, Taylor & Francis Journals, vol. 36(1), pages 9-27, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marletto, Gerardo, 2011. "Structure, agency and change in the car regime. A review of the literature," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 47, pages 71-88.
    2. Zhu, Siying & Zhu, Feng, 2019. "Cycling comfort evaluation with instrumented probe bicycle," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 217-231.
    3. Gupta, Monika, 2016. "Willingness to pay for carbon tax: A study of Indian road passenger transport," Transport Policy, Elsevier, vol. 45(C), pages 46-54.
    4. Ospina, Juan P. & Duque, Juan C. & Botero-Fernández, Verónica & Montoya, Alejandro, 2022. "The maximal covering bicycle network design problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 222-236.
    5. Hong, Jinhyun & Philip McArthur, David & Stewart, Joanna L., 2020. "Can providing safe cycling infrastructure encourage people to cycle more when it rains? The use of crowdsourced cycling data (Strava)," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 109-121.
    6. Ali Al-Ramini & Mohammad A Takallou & Daniel P Piatkowski & Fadi Alsaleem, 2022. "Quantifying changes in bicycle volumes using crowdsourced data," Environment and Planning B, , vol. 49(6), pages 1612-1630, July.
    7. Caicedo, Angélica & Estrada, Miquel & Medina-Tapia, Marcos & Mayorga, Miguel, 2023. "Optimizing bike network design: A cost-effective methodology for heterogeneous travel demands using continuous approximation techniques," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    8. Arellana, Julián & Saltarín, María & Larrañaga, Ana Margarita & González, Virginia I. & Henao, César Augusto, 2020. "Developing an urban bikeability index for different types of cyclists as a tool to prioritise bicycle infrastructure investments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 310-334.
    9. Focas, Caralampo, 2016. "Travel behaviour and CO2 emissions in urban and exurban London and New York," Transport Policy, Elsevier, vol. 46(C), pages 82-91.
    10. Bas, Javier & Al-Khasawneh, Mohammad B. & Erdoğan, Sevgi & Cirillo, Cinzia, 2023. "How the design of Complete Streets affects mode choice: Understanding the behavioral responses to the level of traffic stress," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    11. Álvarez-Antelo, David & Lauer, Arthur & Capellán-Pérez, Íñigo, 2024. "Exploring the potential of a novel passenger transport model to study the decarbonization of the transport sector," Energy, Elsevier, vol. 305(C).
    12. Can Cui & Yu Zhang, 2024. "Integration of Shared Micromobility into Public Transit: A Systematic Literature Review with Grey Literature," Sustainability, MDPI, vol. 16(9), pages 1-18, April.
    13. Hill, Chris & Young, Marcus & Blainey, Simon & Cavazzi, Stefano & Emberson, Chris & Sadler, Jason, 2024. "An integrated geospatial data model for active travel infrastructure," Journal of Transport Geography, Elsevier, vol. 117(C).
    14. Krystian Pietrzak & Oliwia Pietrzak, 2022. "Tram System as a Challenge for Smart and Sustainable Urban Public Transport: Effects of Applying Bi-Directional Trams," Energies, MDPI, vol. 15(15), pages 1-29, August.
    15. Van Veghel, Daniel & Scott, Darren M., 2024. "Investigating the impacts of bike lanes on bike share ridership: A holistic approach and demonstration," Journal of Transport Geography, Elsevier, vol. 115(C).
    16. Juseung Lee & Ducksu Seo, 2022. "Influences of Urban Bikeway Design and Land Use on Bike Collision Severity: Evidence from Pohang in South Korea," Sustainability, MDPI, vol. 14(14), pages 1-14, July.
    17. Osama, Ahmed & Sayed, Tarek & Bigazzi, Alexander Y., 2017. "Models for estimating zone-level bike kilometers traveled using bike network, land use, and road facility variables," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 14-28.
    18. Faghih Imani, Ahmadreza & Miller, Eric J. & Saxe, Shoshanna, 2019. "Cycle accessibility and level of traffic stress: A case study of Toronto," Journal of Transport Geography, Elsevier, vol. 80(C).
    19. Ülengin, Füsun & Işık, Mine & Ekici, Şule Önsel & Özaydın, Özay & Kabak, Özgür & Topçu, Y. İlker, 2018. "Policy developments for the reduction of climate change impacts by the transportation sector," Transport Policy, Elsevier, vol. 61(C), pages 36-50.
    20. Broadstock, David C. & Collins, Alan, 2010. "Measuring unobserved prices using the structural time-series model: The case of cycling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(4), pages 195-200, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:11:p:4631-:d:1404964. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.