Abstract:
As open source volunteered geographic information continues to gain popularity, the user community and data contributions are expected to grow, e.g. CloudMade, Apple, and Ushahidi now provide OpenStreetMap© (OSM) as a base layer for some of their mapping applications. This, coupled with the lack of cartographic and data quality standards and the expectation to one day be able to use this vector data for more geopositionally sensitive applications, like GPS navigation, leaves potential users and researchers to question the accuracy of the database. This research takes a photogrammetric approach to determining the positional accuracy of OSM road features using stereo imagery and a vector adjustment model. The method applies rigorous analytical measurement principles to compute accurate real world geolocations of OSM road shape points. After adjustment, the absolute positional accuracy of a road vector can be described by the Root Mean Square Error (RMSE) value of the shape point residuals. In addition, adjusted shape point locations and the statistical confidence in those positions (CE/LE 90) are computed. It is also suggested that once this information is known about the vector data, it should be carried along with and recorded as an attribute at the feature level, thereby providing useful provenance and increasing the overall utility of the database.
