Quality Evaluation of VGI Using Authoritative Data - A Comparison with Land Use Data in Southern Germany

Volunteered Geographic Information (VGI) such as data derived from the OpenStreetMap (OSM) project is a popular data source for freely available geographic data. Normally, untrained contributors gather these data. This fact is frequently a cause of concern regarding the quality and usability of such data. In this study, the quality of OSM land use and land cover (LULC) data is investigated for an area in southern Germany. Two spatial data quality elements, thematic accuracy and completeness are addressed by comparing the OSM data with an authoritative German reference dataset. The results show that the kappa value indicates a substantial agreement between the OSM and the authoritative dataset. Nonetheless, for our study region, there are clear variations between the LULC classes. Forest covers a large area and shows both a high OSM completeness (97.6%) and correctness (95.1%). In contrast, farmland also covers a large area, but for this class OSM shows a low completeness value (45.9%) due to unmapped areas. Additionally, the results indicate that a high population density, as present in urbanized areas, seems to denote a higher strength of agreement between OSM and the DLM (Digital Landscape Model). However, a low population density does not necessarily imply a low strength of agreement.

[1]  Anita Graser,et al.  Towards an Open Source Analysis Toolbox for Street Network Comparison: Indicators, Tools and Results of a Comparison of OSM and the Official Austrian Reference Graph , 2014, Trans. GIS.

[2]  Henri J G L Aalders The Registration of Quality in a GIS , 2002 .

[3]  Angi Voß,et al.  A Comparison of the Street Networks of Navteq and OSM in Germany , 2011, AGILE Conf..

[4]  François Vauglin,et al.  A Practical Study on Precision and Resolution in Vector Geographical Databases , 2002 .

[5]  Monika Sester,et al.  Quality Analysis of OpenStreetMap Data Based on Application Needs , 2011, Cartogr. Int. J. Geogr. Inf. Geovisualization.

[6]  Eric Vaz,et al.  An assessment of a collaborative mapping approach for exploring land use patterns for several European metropolises , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[7]  Jacob Cohen A Coefficient of Agreement for Nominal Scales , 1960 .

[8]  Robert Hecht,et al.  Measuring Completeness of Building Footprints in OpenStreetMap over Space and Time , 2013, ISPRS Int. J. Geo Inf..

[9]  Pascal Neis,et al.  A Comprehensive Framework for Intrinsic OpenStreetMap Quality Analysis , 2014, Trans. GIS.

[10]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[11]  Pascal Neis,et al.  Quality assessment for building footprints data on OpenStreetMap , 2014, Int. J. Geogr. Inf. Sci..

[12]  A. Zipf,et al.  Comparative Spatial Analysis of Positional Accuracy of OpenStreetMap and Proprietary Geodata , 2012 .

[13]  Miriam J. Metzger,et al.  The credibility of volunteered geographic information , 2008 .

[14]  Peter Mooney,et al.  Characterising the metric and topological evolution of OpenStreetMap network representations , 2013, The European Physical Journal Special Topics.

[15]  K. Shadan,et al.  Available online: , 2012 .

[16]  Michael Auer,et al.  An Algorithm Based Methodology for the Creation of a Regularly Updated Global Online Map Derived From Volunteered Geographic Information , 2012 .

[17]  M. Haklay How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets , 2010 .

[18]  A. Zipf,et al.  A Comparative Study of Proprietary Geodata and Volunteered Geographic Information for Germany , 2010 .

[19]  Pascal Neis,et al.  Assessing the Effect of Data Imports on the Completeness of OpenStreetMap – A United States Case Study , 2013, Trans. GIS.

[20]  Christian Heipke,et al.  EVALUATION OF AUTOMATIC ROAD EXTRACTION , 2007 .

[21]  M. Goodchild Citizens as sensors: the world of volunteered geography , 2007 .

[22]  Adam C. Winstanley,et al.  Towards quality metrics for OpenStreetMap , 2010, GIS '10.

[23]  Carola Kunze,et al.  Zur Vollständigkeit des Gebäudedatenbestandes von OpenStreetMap , 2013, KN - Journal of Cartography and Geographic Information.

[24]  Pascal Neis,et al.  The Street Network Evolution of Crowdsourced Maps: OpenStreetMap in Germany 2007-2011 , 2011, Future Internet.

[25]  Amir Pourabdollah,et al.  Towards an Authoritative OpenStreetMap: Conflating OSM and OS OpenData National Maps' Road Network , 2013, ISPRS Int. J. Geo Inf..

[26]  Pascal Neis,et al.  Recent Developments and Future Trends in Volunteered Geographic Information Research: The Case of OpenStreetMap , 2014, Future Internet.

[27]  Gary J. Hunter,et al.  New Tools For Handling Spatial Data Quality : Moving from Academic Concepts to Practical Reality , 1999 .

[28]  Guillaume Touya,et al.  Inferring the Scale of OpenStreetMap Features , 2015, OpenStreetMap in GIScience.

[29]  Robert Jeansoulin,et al.  Towards spatial data quality information analysis tools for experts assessing the fitness for use of spatial data , 2007, Int. J. Geogr. Inf. Sci..

[30]  Christian Heipke,et al.  Crowdsourcing geospatial data , 2010 .

[31]  David Fairbairn,et al.  Assessing similarity matching for possible integration of feature classifications of geospatial data from official and informal sources , 2012, Int. J. Geogr. Inf. Sci..

[32]  Guillaume Touya,et al.  Quality Assessment of the French OpenStreetMap Dataset , 2010, Trans. GIS.

[33]  MICHAEL F. GOODCHILD,et al.  A Simple Positional Accuracy Measure for Linear Features , 1997, Int. J. Geogr. Inf. Sci..

[34]  Russell G. Congalton,et al.  A review of assessing the accuracy of classifications of remotely sensed data , 1991 .

[35]  Pascal Neis,et al.  Updating digital elevation models via change detection and fusion of human and remote sensor data in urban environments , 2015, Int. J. Digit. Earth.

[36]  Giles M. Foody,et al.  Status of land cover classification accuracy assessment , 2002 .

[37]  Vyron Antoniou,et al.  How Many Volunteers Does it Take to Map an Area Well? The Validity of Linus’ Law to Volunteered Geographic Information , 2010 .

[38]  David Fairbairn,et al.  Assessing the accuracy of 'crowdsourced' data and its integration with official spatial data sets , 2010 .