Matching authority and VGI road networks using an extended node-based matching algorithm
The amount of volunteered geographic information (VGI) has increased over the past decade, and several studies have been conducted to evaluate the quality of VGI data. In this study, we evaluate the completeness of the road network in the VGI data set OpenStreetMap (OSM). The evaluation is based on...
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| Published in | Geo-spatial information science Vol. 18; no. 2-3; pp. 65 - 80 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Taylor & Francis
03.07.2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1009-5020 1993-5153 1993-5153 |
| DOI | 10.1080/10095020.2015.1071065 |
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| Abstract | The amount of volunteered geographic information (VGI) has increased over the past decade, and several studies have been conducted to evaluate the quality of VGI data. In this study, we evaluate the completeness of the road network in the VGI data set OpenStreetMap (OSM). The evaluation is based on an accurate and efficient network-matching algorithm. The study begins with a comparison of the two main strategies for network matching: segment-based and node-based matching. The comparison shows that the result quality is comparable for the two strategies, but the node-based result is considerably more computationally efficient. Therefore, we improve the accuracy of node-based algorithm by handling topological relationships and detecting patterns of complicated network components. Finally, we conduct a case study on the extended node-based algorithm in which we match OSM to the Swedish National Road Database (NVDB) in Scania, Sweden. The case study reveals that OSM has a completeness of 87% in the urban areas and 69% in the rural areas of Scania. The accuracy of the matching process is approximately 95%. The conclusion is that the extended node-based algorithm is sufficiently accurate and efficient for conducting surveys of the quality of OSM and other VGI road data sets in large geographic regions. |
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| AbstractList | The amount of volunteered geographic information (VGI) has increased over the past decade, and several studies have been conducted to evaluate the quality of VGI data. In this study, we evaluate the completeness of the road network in the VGI data set OpenStreetMap (OSM). The evaluation is based on an accurate and efficient network-matching algorithm. The study begins with a comparison of the two main strategies for network matching: segment-based and node-based matching. The comparison shows that the result quality is comparable for the two strategies, but the node-based result is considerably more computationally efficient. Therefore, we improve the accuracy of node-based algorithm by handling topological relationships and detecting patterns of complicated network components. Finally, we conduct a case study on the extended node-based algorithm in which we match OSM to the Swedish National Road Database (NVDB) in Scania, Sweden. The case study reveals that OSM has a completeness of 87% in the urban areas and 69% in the rural areas of Scania. The accuracy of the matching process is approximately 95%. The conclusion is that the extended node-based algorithm is sufficiently accurate and efficient for conducting surveys of the quality of OSM and other VGI road data sets in large geographic regions. |
| Author | Mansourian, Ali Abdolmajidi, Ehsan Harrie, Lars Will, Julian |
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| SubjectTerms | Algorithms Earth and Related Environmental Sciences geographic data Geovetenskap och relaterad miljövetenskap Human Geography Kulturgeografi Mapping Matching Natural Sciences Naturgeografi Naturvetenskap Networks node-based matching Open systems OpenStreetMap (OSM) pattern detection Physical Geography Roads Samhällsvetenskap segment-based matching Social and Economic Geography Social och ekonomisk geografi Social Sciences Strategy Swedish National Road Database (NVDB) volunteered geographic information (VGI) |
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| Title | Matching authority and VGI road networks using an extended node-based matching algorithm |
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