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Multi-granular Street Network Representation towards Quality Assessment of OpenStreetMap Data
7 references·12 citing·28 second hop
Multi-granular Street Network Representation towards Quality Assessment of OpenStreetMap Data (2013)Multi-granular Street Network Representat…Analysing the growth of OpenStreetMap networks (2013)Analysing the growth of OpenS…Assuring the quality of volunteered geographic information (2012)Assuring the quality of volun…Assessing Data Completeness of VGI through an Automated Matching Procedure for Linear Data (2012)Assessing Data Completeness o…Quality Assessment of the French OpenStreetMap Dataset (2010)Quality Assessment of the Fre…How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets (2010)How Good is Volunteered Geogr…Comparison of the accuracy of OpenStreetMap for Ireland with Google Maps and Bing Maps (2010)Comparison of the accuracy of…OpenStreetMap: User-Generated Street Maps (2008)OpenStreetMap: User-Generated…Towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases (2021)Towards detecting, characteri…GeoDart: A System for Discovering Maps Discrepancies (2021)GeoDart: A System for Discove…Developing a multi-classifier system to classify OSM tags based on centrality parameters (2021)Developing a multi-classifier…BITOUR: A Business Intelligence Platform for Tourism Analysis (2020)BITOUR: A Business Intelligen…Traditional vs. Machine-Learning Techniques for OSM Quality Assessment (2019)Traditional vs. Machine-Learn…Combining Road Network Data from OpenStreetMap with an Authoritative Database (2018)Combining Road Network Data f…An Automated Approach for Quality Assessment of OpenStreetMap Data (2018)An Automated Approach for Qua…A Multi-layer CRF Based Methodology for Improving Crowdsourced Street Semantics (2018)A Multi-layer CRF Based Metho…Traditional vs. Machine-Learning Techniques for OSM Quality Assessment (2017)Traditional vs. Machine-Learn…Automatic Tag Enrichment for Points-of-Interest in Open Street Map (2017)Automatic Tag Enrichment for …Machine Learning for Crowdsourced Spatial Data (2016)Machine Learning for Crowdsou…Probabilistic Graphical Modelling for Semantic Labelling of Crowdsourced Map Data (2015)Probabilistic Graphical Model…Citizens as Voluntary Sensors: Spatial Data Infrastructure in the World of Web 2.0 (2007)A review of volunteered geographic information quality assessment methods (2016)The world’s user-generated road map is more than 80% complete (2017)Global maps of travel time to healthcare facilities (2020)The world is flat: a brief history of the twenty-first century (2006)How Many Volunteers Does it Take to Map an Area Well? The Validity of Linus’ Law to Volunteered Geographic Information (2010)Volunteered Geographic Information and Crowdsourcing Disaster Relief: A Case Study of the Haitian Earthquake (2010)Citizens as sensors: the world of volunteered geography (2007)Crowdsourcing geographic information for disaster response: a research frontier (2010)Analysis of Interaction and Co‐editing Patterns amongst O pen S treet M ap Contributors (2013)Corporate Editors in the Evolving Landscape of OpenStreetMap (2019)OpenStreetMap history for intrinsic quality assessment: Is OSM up-to-date? (2019)Central Places in Southern Germany (1967)A Computer Movie Simulating Urban Growth in the Detroit Region (1970)Key issues and research priorities for public participation GIS (PPGIS): A synthesis based on empirical research (2013)Geospatial big data handling theory and methods: A review and research challenges (2015)Destination Competitiveness: Determinants and Indicators (2003)Real-time routing with OpenStreetMap data (2011)What do we know about social media in tourism? A review (2014)A Coefficient of Agreement for Nominal Scales (1960)Inferring freeway traffic volume with spatial interaction enhanced betweenness centrality (2024)A Quality Study of the OpenStreetMap Dataset for Tehran (2014)Assessing VGI Data Quality (2017)A New Method for the Assessment of Spatial Accuracy and Completeness of OpenStreetMap Building Footprints (2018)Assessing the Effect of Data Imports on the Completeness of OpenStreetMap – A U nited S tates Case Study (2013)Quality Assessment of the Contributed Land Use Information from OpenStreetMap Versus Authoritative Datasets (2015)Researching Volunteered Geographic Information: Spatial Data, Geographic Research, and New Social Practice (2011)Citizen Science and Volunteered Geographic Information: Overview and Typology of Participation (2012)
this work references cited by second hop

References

  • 2008OpenStreetMap: User-Generated Street Maps3,219 cited
  • 2010How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets1,640 cited
  • 2012Assuring the quality of volunteered geographic information773 cited
  • 2010Quality Assessment of the French OpenStreetMap Dataset668 cited
  • 2012Assessing Data Completeness of VGI through an Automated Matching Procedure for Linear Data155 cited
  • 2010Comparison of the accuracy of OpenStreetMap for Ireland with Google Maps and Bing Maps152 cited
  • 2013Analysing the growth of OpenStreetMap networks96 cited

Cited by

  • 2020BITOUR: A Business Intelligence Platform for Tourism Analysis21 cited
  • 2015Probabilistic Graphical Modelling for Semantic Labelling of Crowdsourced Map Data10 cited
  • 2021Developing a multi-classifier system to classify OSM tags based on centrality parameters10 cited
  • 2017Automatic Tag Enrichment for Points-of-Interest in Open Street Map10 cited
  • 2016Machine Learning for Crowdsourced Spatial Data7 cited
  • 2018Combining Road Network Data from OpenStreetMap with an Authoritative Database7 cited
  • 2018An Automated Approach for Quality Assessment of OpenStreetMap Data7 cited

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2021
GeoDart: A System for Discovering Maps Discrepancies
7 cited
  • 2021Towards detecting, characterizing, and rating of road class errors in crowd-sourced road network databases6 cited
  • 2019Traditional vs. Machine-Learning Techniques for OSM Quality Assessment5 cited
  • 2017Traditional vs. Machine-Learning Techniques for OSM Quality Assessment4 cited
  • 2018A Multi-layer CRF Based Methodology for Improving Crowdsourced Street Semantics4 cited