Mapping the Completeness and Positional Accuracy of OpenStreetMap Road Data at the County Level in the Contiguous United States

Abstract

The OpenStreetMap (OSM) project allows volunteers in the community to contribute and manage spatial data collaboratively and provides free spatial data with global coverage to the public. OSM data have been widely used in many applications. However, the quality of OSM data can be inconsistent due to the crowdsourcing nature of the OSM project. This study compares the OSM road data with the national road data from the U.S. Census Topologically Integrated Geographic Encoding and Referencing system (TIGER) project in the contiguous United States. Specifically, we used three indicators to examine the completeness and positional accuracy of the OSM road data at the county level. Then we performed spatial analysis to study the patterns of the discrepancies. Our results show that OSM road data are inconsistent in completeness and positional accuracy across different counties. Finally, we compared the three indicators among metropolitan, nonmetropolitan, and rural counties with Analysis of Variance (ANOVA) and Boxplot. The results show that the OSM road data in metropolitan counties have better completeness and positional accuracy than those in nonmetropolitan and rural counties. This study can improve our understanding of the quality of OSM road data in the United States, which in turn can help the OSM community improve the quality of road data and allow data users to better use OSM road data in different applications.