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Research Articles

A comprehensive quality assessment framework for linear features from Volunteered Geographic Information

ORCID Icon, , ORCID Icon, ORCID Icon, &
Pages 1826-1847 | Received 07 Feb 2020, Accepted 30 Sep 2020, Published online: 12 Oct 2020

References

  • Antoniou, V. and Skopeliti, A., 2015. Measures and indicators of vgi quality: an overview. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, II-3/W5, 345–351. doi:10.5194/isprsannals-II-3-W5-345-2015
  • Barrington-Leigh, C. and Millard-Ball, A., 2017. The world’s user-generated road map is more than 80% complete. Plos One, 14 (10), e0224742. doi:10.1371/journal.pone.0224742
  • Barron, C., Neis, P., and Zipf, A., 2014. A comprehensive framework for intrinsic openstreetmap quality analysis. Transactions in Gis, 18 (6), 877–895. doi:10.1111/tgis.12073
  • Basiri, A., et al., 2019. Crowdsourced geospatial data quality: challenges and future directions. International Journal of Geographical Information Science, 33 (8), 1588–1593. doi:10.1080/13658816.2019.1593422
  • Bergman, C. and Oksanen, J., 2016. Conflation of OpenStreetMap and mobile sports tracking data for automatic bicycle routing. Transactions in Gis, 20 (6), 848–868.
  • Camboim, S., Bravo, J., and Sluter, C., 2015. An investigation into the completeness of, and the updates to, OpenStreetMap data in a heterogeneous area in Brazil. ISPRS International Journal of Geo-Information, 4 (3), 1366–1388. doi:10.3390/ijgi4031366
  • Chehreghan, A. and Abbaspour, R.A., 2018. An evaluation of data completeness of VGI through geometric similarity assessment. International Journal of Image and Data Fusion, 9 (4), 319–337. doi:10.1080/19479832.2018.1504825
  • Ciepłuch, B., et al., 2010. Comparison of the accuracy of OpenStreetMap for Ireland with Google Maps and Bing Maps. Proceedings of the Ninth International Symposium on Spatial Accuracy Assessment in Natural Resuorces and Enviromental Sciences. Leicester, England.
  • Exel, M., Dias, E., and Fruijtier, S., 2010. The impact of crowdsourcing on spatial data quality indicators. In Proceedings of GiScience 2011, 14–17. Zurich, Switzerland.
  • Fairbairn, D. and Al-Bakri, M., 2013. Using geometric properties to evaluate possible integration of authoritative and volunteered geographic information. ISPRS International Journal of Geo-Information, 2 (2), 349–370. doi:10.3390/ijgi2020349
  • Fogliaroni, P., D’Antonio, F., and Clementini, E., 2018. Data trustworthiness and user reputation as indicators of VGI quality. Geo-Spatial Information Science, 21 (3), 213–233. doi:10.1080/10095020.2018.1496556
  • Fonte, C.C., et al., 2015. Usability of VGI for validation of land cover maps. International Journal of Geographical Information Science, 29 (7), 1269–1291. doi:10.1080/13658816.2015.1018266
  • Forghani, M. and Delavar, M.R., 2014. A quality study of the OpenStreetMap dataset for Tehran. ISPRS International Journal of Geo-Information, 3 (2), 750–763. doi:10.3390/ijgi3020750
  • Gardner, Z. and Mooney, P., 2018. Investigating gender differences in OpenStreetMap activities in Malawi: a small case-study. AGILE Conference. Lund, Sweden.
  • Girres, J.F. and Touya, G., 2010. Quality assessment of the French OpenStreetMap dataset. Transactions in Gis, 14 (4), 435–459. doi:10.1111/j.1467-9671.2010.01203.x
  • Goodchild, M. and Gopal, S., 1989. The accuracy of spatial database. London: Taylor and Francis
  • Goodchild, M., Haining, R., and Wise, S., 1992. Integrating GIS and spatial data analysis: problems and possibilities. International Journal of Geographical Information Systems, 6 (5), 407–423. doi:10.1080/02693799208901923
  • Goodchild, M.F., 2007. Citizens as Sensors: the world of volunteered geography. Geojournal, 69 (4), 211–221. doi:10.1007/s10708-007-9111-y
  • Goodchild, M.F. and Glennon, J.A., 2010. Crowdsourcing geographic information for disaster response: a research frontier. International Journal of Digital Earth, 3 (3), 231–241. doi:10.1080/17538941003759255
  • Goodchild, M.F. and Hunter, G.J., 1997. A simple positional accuracy measure for linear features. International Journal of Geographical Information Science, 11 (3), 299–306. doi:10.1080/136588197242419
  • Goodchild, M.F. and Li, L.N., 2012. Assuring the quality of volunteered geographic information. Spatial Statistics, 1, 110–120. doi:10.1016/j.spasta.2012.03.002
  • Haklay, M., 2010. How good is volunteered geographical information? A comparative study of OpenStreetMap and ordnance survey datasets. Environment and Planning. B, Planning & Design, 37, 682–703. doi:10.1068/b35097
  • Haklay, M., 2016. Why is participation inequality important? London: Ubiquity Press.
  • Hashemi, P. and Abbaspour, R.A., 2015. Assessment of logical consistency in OpenStreetMap based on the spatial similarity concept. Switzerland: Springer International Publishing Switzerland.
  • Hong, Y. and Yao, Y., 2019. Hierarchical community detection and functional area identification with OSM roads and complex graph theory. International Journal of Geographical Information Science, 33 (8), 1569–1587. doi:10.1080/13658816.2019.1584806
  • Hunter, G.J. 1999. New tools for handling spatial data quality: moving from academic concepts to practical reality. URISA 1999 Conference. Chicago, 167–180.
  • ISO, 2002. ISO 19113: 2002. Geographic information — quality principles. Geneva: ISO
  • Jackson, S., et al., 2013. Assessing completeness and spatial error of features in volunteered geographic information. ISPRS International Journal of Geo-Information, 2 (2), 507. doi:10.3390/ijgi2020507
  • Kalantari, M., and La, V. 2015. Assessing OpenStreetMap as an open property map. In: J. Jokar Arsanjani, A. Zipf, P. Mooney, and M. Helbich , eds. OpenStreetMap in GIScience, Lecture Notes in Geoinformation and Cartography. Cham: Springer, 255–272.
  • Keßler, C. and Groot, R.T.A.D., 2013. Trust as a proxy measure for the quality of volunteered geographic information in the case of OpenStreetMap. In: D. Vandenbroucke, B. Bucher, and J. Crompvoets, eds.. Geographic Information Science at the Heart of Europe. Lecture Notes in Geoinformation and Cartography. Cham: Springer, 21–37
  • Koukoletsos, T., Haklay, M., and Ellul, C., 2012. Assessing data completeness of VGI through an automated matching procedure for linear data. Transactions in Gis, 16 (4), 477–498. doi:10.1111/j.1467-9671.2012.01304.x
  • Kuhn, H.W. and Kuenne, K.E., 1962. An efficient algorithm for the numerical solution of the generalized Weber problem in spatial economics. Journal of Regional Science, 4 (2), 21–34.
  • Lee, M., et al., 2017. Morphology of travel routes and the organization of cities. Nature Communications, 8 (1), 2229. doi:10.1038/s41467-017-02374-7
  • Lin, A., et al., 2020. A big data-driven dynamic estimation model of relief supplies demand in urban flood disaster. International Journal of Disaster Risk Reduction, 49, 101682.
  • Ma, D., Sandberg, M., and Jiang, B., 2015. Characterizing the heterogeneity of the OpenStreetMap data and community. ISPRS International Journal of Geo-Information, 4 (2), 535–550. doi:10.3390/ijgi4020535
  • Manandhar, P., et al., 2019. Towards automatic extraction and updating of VGI-based road networks using deep learning. Remote Sensing, 11 (9), 1012–1122. doi:10.3390/rs11091012
  • Mobasheri, A., et al., 2017. Are crowdsourced datasets suitable for specialized routing services? Case study of openstreetmap for routing of people with limited mobility. Sustainability, 9 (6), 997. doi:10.3390/su9060997
  • Mobasheri, A., et al., 2018a. Enrichment of OpenStreetMap data completeness with sidewalk geometries using data mining techniques. Sensors, 18 (2), 509. doi:10.3390/s18020509
  • Mobasheri, A., Zipf, A., and Francis, L., 2018b. OpenStreetMap data quality enrichment through awareness raising and collective action tools-experiences from a European project. Geo-Spatial Information Science, 21 (3), 234–246. doi:10.1080/10095020.2018.1493817
  • Mocnik, F.-B., et al., 2018. A grounding-based ontology of data quality measures. Journal Of Spatial Information Science, 16, 1–25.
  • Moeinaddini, M., Asadi-Shekari, Z., and Shah, M.Z., 2014. The relationship between urban street networks and the number of transport fatalities at the city level. Safety Science, 62, 114–120. doi:10.1016/j.ssci.2013.08.015
  • Mullen, W.F., et al., 2014. Assessing the impact of demographic characteristics on spatial error in volunteered geographic information features. Geojournal, 80, 587–605. doi:10.1007/s10708-014-9564-8
  • Neis, P. and Zielstra, D., 2014. Recent developments and future trends in volunteered geographic information research: the case of OpenStreetMap. Future Internet, 6 (1), 76–106. doi:10.3390/fi6010076
  • Neis, P., Zielstra, D., and Zipf, A., 2012. The street network evolution of crowdsourced maps: openStreetMap in Germany 2007–2011. Future Internet, 4 (1), 1–21. doi:10.3390/fi4010001
  • Neis, P., Zielstra, D., and Zipf, A., 2013. Comparison of volunteered geographic information data contributions and community development for selected world regions. Future Internet, 5 (2), 282–300. doi:10.3390/fi5020282
  • OSM, 2020a. Commercial OSM Software and Services [online]. Available from: https://wiki.openstreetmap.org/wiki/Commercial_OSM_Software_and_Services [Accessed 20 May 2020].
  • OSM, 2020b. Quality assurance [online]. Available from: https://wiki.openstreetmap.org/wiki/Quality_assurance [Accessed 20 May 2020]
  • Safra, E., et al., 2010. Location-based algorithms for finding sets of corresponding objects over several geo-spatial data sets. International Journal of Geographical Information Science, 24 (1), 69–106. doi:10.1080/13658810802275560
  • Sehra, S.S., et al., 2019. Extending processing toolbox for assessing the logical consistency of OpenStreetMap data. Transactions in Gis, 24 (1), 44–71. doi:10.1111/tgis.12587
  • Sehra, S.S., Singh, J., and Rai, H.S., 2016. Analysing OpenStreetMap data for topological errors. International Journal of Spatial, Temporal and Multimedia Information Systems, 1 (1), 87–101. doi:10.1504/IJSTMIS.2016.076800
  • Senaratne, H., et al., 2017. A review of volunteered geographic information quality assessment methods. International Journal of Geographical Information Science, 31 (1), 139–167. doi:10.1080/13658816.2016.1189556
  • Seo, S., O’Hara, and O’Hara, C.G., 2009. Quality assessment of linear data. International Journal of Geographical Information Science, 23 (12), 1503–1525. doi:10.1080/13658810802231456
  • Severinsen, J., et al., 2019. VGTrust: measuring trust for volunteered geographic information. International Journal of Geographical Information Science, 33 (8), 1683–1701. doi:10.1080/13658816.2019.1572893
  • Sreelekha, M.G., Krishnamurthy, K., and Anjaneyulu, M.V.L.R., 2017. Fractal Assessment of Road Transport System. European Transport, 65, 5.
  • Stark, H.J., 2010. Quality Assessment of Volunteered Geographic Information (VGI) Based on Open Web Map Services and ISO/TC 211 19100-Family Standards. FOSS4G. Barcelona, Spain.
  • Truong, Q.T., de Runz, C., and Touya, G., 2019. Analysis of collaboration networks in OpenStreetMap through weighted social multigraph mining. International Journal of Geographical Information Science, 33 (8), 1651–1682. doi:10.1080/13658816.2018.1556395
  • Vauglin, F., 1997. Modèles statistiques des imprécisions géométriques des objets géographiques linéaires. PhD. Université de Marne-la-Vallée.
  • Wu, H., et al., 2014. Assessing the effects of land use spatial structure on urban heat islands using HJ-1B remote sensing imagery in Wuhan, China. International Journal of Applied Earth Observation and Geoinformation, 32, 67–78. doi:10.1016/j.jag.2014.03.019
  • Wu, H., et al., 2019. Examining the sensitivity of spatial scale in cellular automata Markov chain simulation of land use change. International Journal of Geographical Information Science, 33 (5), 1040–1061. doi:10.1080/13658816.2019.1568441
  • Xie, F. and Levinson, D., 2007. Measuring the structure of road networks. Geographical Analysis, 39 (3), 336–356. doi:10.1111/j.1538-4632.2007.00707.x
  • Yan, Y.W., et al., 2020. Volunteered geographic information research in the first decade: a narrative review of selected journal articles in GIScience. International Journal of Geographical Information Science, 34 (9), 1765–1791. doi:10.1080/13658816.2020.1730848
  • Yang, C., et al., 2020. Big spatiotemporal data analytics: a research and innovation frontier. International Journal of Geographical Information Science, 34 (6), 1075–1088. doi:10.1080/13658816.2019.1698743
  • Zhang, W.-B., Leung, Y., and Ma, J.-H., 2019. Analysis of positional uncertainty of road networks in volunteered geographic information with a statistically defined buffer-zone method. International Journal of Geographical Information Science, 33 (9), 1807–1828. doi:10.1080/13658816.2019.1606430
  • Zhang, Y., et al., 2015. Density and diversity of OpenStreetMap road networks in China. Journal of Urban Management, 4 (2), 135–146. doi:10.1016/j.jum.2015.10.001
  • Zheng, Y. and Izzat, I.H., 2018. Exploring OpenStreetMap capability for road perception. 2018 IEEE Intelligent Vehicles Symposium. Changshu, Suzhou, China, 1438–1443.
  • Zheng, Y., Izzat, I.H., and Hansen, J.H.L., 2019. Exploring OpenStreetMap availability for driving environment understanding. preprint, arXiv:1903.04084.
  • Zhou, Q., 2018. Exploring the relationship between density and completeness of urban building data in OpenStreetMap for quality estimation. International Journal of Geographical Information Science, 32 (2), 257–281. doi:10.1080/13658816.2017.1395883
  • Zhou, Q. and Tian, Y., 2018. The use of geometric indicators to estimate the quantitative completeness of street blocks in OpenStreetMap. Transactions in GIS, 22 (6), 1550–1572. doi:10.1111/tgis.12486
  • Zielstra, D., Hochmair, H.H., and Neis, P., 2013. Assessing the effect of data imports on the completeness of OpenStreetMap – A United States case study. Transactions in GIS, 17 (3), 315–334. doi:10.1111/tgis.12037
  • Zielstra, D. and Zipf, A., A comparative study of proprietary geodata and volunteered geographic information for Germany. ed. Proceedings of the Thirteenth AGILE International Conference on Geographic Information Science, 2010 Guimarães, Portugal.

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