Abstract
OpenStreetMap (OSM) is mostly a good map for viewers to look at but it lacks of sufficient quality in certain applications like navigation. Quality issues are usually related to how roads are ‘drawn’ (modeled) by OSM contributors. First of all, this paper identifies several issues in tagging and modeling OSM road network by case studies, and also gives suggestions for contributors and routing service providers. As a key contribution, this paper proposes a methodology to evaluate OSM roads that does not rely on reference data or ground truth. The evaluation aims not only to identify errors in OSM data, but also to give more intelligent suggestions based on the information available in the spatial context of the problematic data. More specifically, named roads are recognized based on the concept of “stroke”. Missing or incorrect names can be found by outlier detection within the scope of the named roads. Such an idea can be widely applied to detect inconsistent tags and provide intelligent suggestions for data correction.
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Acknowledgments
We thank the anonymous reviewers for their valuable comments which substantially improved this paper. This work was financially supported by National Natural Science Foundation of China (Grant No. 41301410) and China Postdoctoral Science Foundation funded project (Grant No. 2013M531742).
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Zhang, X., Ai, T. (2015). How to Model Roads in OpenStreetMap? A Method for Evaluating the Fitness-for-Use of the Network for Navigation. In: Harvey, F., Leung, Y. (eds) Advances in Spatial Data Handling and Analysis. Advances in Geographic Information Science. Springer, Cham. https://doi.org/10.1007/978-3-319-19950-4_9
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DOI: https://doi.org/10.1007/978-3-319-19950-4_9
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