Ziya Alsayyed

The quality of road data is important as they are widely used in scientific explorations andpractical applications. In this study, quantitative assessments of several quality criteria are conducted on two road datasets: Ontario Road Network (ORN), and DMTI CanMap RouteLogistics. A buffer and overlay analysis technique is used to estimate the completeness of the ORN dataset. The process revealed that the ORN has 80.3% completeness and 2% miscoding. The completeness test has allowed for editing the data for the evaluation of the positional accuracy. An iterative buffer and overlay technique was carried out to estimate the average displacement between the two datasets. Average displacements of 4 metres and 2 metres were found for the Gardiner Expressway and the complete dataset for the study area, respectively. Attribute accuracies of the two road datasets were also investigated. It was found that two attributes (name and suffix) of the two datasets do not match by 2.3% for the DMTI and 5.2% for the ORN. Five reasons for attribute inaccuracy were established: spelling, spacing, different-name, different suffix, and no-name.