A Comparison of Feature Density for Large Scale Online Maps

Abstract

Large scale maps as provided by Google, Microsoft Bing, and Mapbox among others provide users an important source of information for local environments. Comparing maps from these services helps to evaluate both the quality of the underlying spatial data and the rendering process. A comparison procedure is used that generates large scale map pairs at random locations using the Application Programmer Interface (API) for three different mapping services. The quality of each representation is then evaluated for feature and label density. The comparison is done for three different continents. For North America, it was found that maps from Google had consistently higher feature and label density than those from Microsoft Bing and Mapbox. Google Maps also held an advantage in Europe. Maps from Microsoft Bing were more detailed in Sub-Saharan Africa in comparison to both Google Maps and Mapbox. Maps from Mapbox, that relies exclusively on data from OpenStreetMap, had the lowest feature and label density for all three areas.