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

Johannes Schering (), Pascal Säfken and Jorge Marx Gómez
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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

Sustainability, 2024, vol. 16, issue 11, 1-14

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.

Keywords: traffic data; geo-referencing; geo-coordinates; traffic volume; cycling data; QGIS; GeoTIFF; reference point; cycling planning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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