Quality Assessment of OpenStreetMap Road Network Data Using Multisourced Data Matching and Conflation
In view of the growing need of quality assessment of crowdsourced geographic information for data acqui-sition in making global navigation map,OpenStreetMap(OSM),which has the highest coverage in the world,is selected to carry out the research of data quality assessment method,and an entity-level quality assessment frame-work is proposed for OSM road network data through utilizing vector road network data and satellite remote sensing imagery as reference data,in which automatic matching,conflating,comparing,and analyzing for the target crowdsourced data and the reference data with quality indicators of data completeness,thematic accuracy,and po-sitioning accuracy.Two German cities are selected as experimental areas,and commercial navigation data and high-resolution satellite remote sensing images are used as reference data,respectively.The experimental results show that the proposed method not only improves the traditional grid-based quality assessment and realizes the ref-erence-based quality assessment of OSM data at the road entity granularity,but also introduces satellite remote sensing images as the assessment reference data,which facilitates the application of the assessment framework in the regions lacking vector reference data of road network.And it can provide a more applicable and more automatic entity-level technical solution for quality auditing and editing of crowdsourced data,which helps to improve the current practices of navigation map data acquisition that heavily relies on labor-intensive quality inspection.
万方数据
维普
