Travel Impedance Agreement among Online Road Network Data Providers

Delmelle, Eric M.; Marsh, Derek M.; Dony, C.; & Delamater, Paul L. (Forthcoming). Travel Impedance Agreement among Online Road Network Data Providers. International Journal of Geographical Information Science, 33(6), 1251-69.

Delmelle, Eric M.; Marsh, Derek M.; Dony, C.; & Delamater, Paul L. (Forthcoming). Travel Impedance Agreement among Online Road Network Data Providers. International Journal of Geographical Information Science, 33(6), 1251-69.

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Online mapping providers offer unprecedented access to spatial data and analytical tools; however, the number of analytical queries that can be requested is usually limited. As such, Volunteered Geographic Information (VGI) services offer a viable alternative, provided that the quality of the underlying spatialtheir data is adequate. In this paper, we evaluate the agreement in travel impedance between estimates from MapQuest Open, which embraces OpenStreetMap (OSM) data?a is based on VGI datasetfrom OpenStreetMap (OSM), and estimates from two other popular commercial providers, namely Google Maps? and ArcGIS? Online. Our framework is articulated around three components, which simulates potentialcalculates shortest routes, estimates their travel impedance using a routing service Application Program Interface (API), and extracts the average number of contributors for each route. We develop an experimental setup with a simulated dataset for the state of North Carolina. Our results suggest a strong correlation of travel impedance among all three road network providers. and that travel impedanceThe agreement is the greatest in areas with a denser road network and the smallest for routes of shorter distances. Most importantly, tTravel estimates from MapQuest Open are nearly identical to both commercial providers when the average number of OSM contributors along the route is larger. The latter finding contributes to a growing body of literature on Linus?s law, recognizing that a larger group of contributors holds the potential to validate and correct inherent errors to the source dataset.




JOUR



Delmelle, Eric M.
Marsh, Derek M.
Dony, C.
Delamater, Paul L.



Forthcoming


International Journal of Geographical Information Science

33

6

1251-69










11881

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