Abstract
With volunteered geographic information (VGI) platforms such as OpenStreetMap (OSM) becoming increasingly popular, we are faced with the challenge of assessing the quality of their content, in order to better understand its place relative to the authoritative content of more traditional sources. Until now, studies have focused primarily on developed countries, showing that VGI content can match or even surpass the quality of authoritative sources, with very few studies in developing countries. In this paper, we compare the quality of authoritative (data from the Regional Center for Mapping of Resources for Development (RCMRD)) and non-authoritative (data from OSM and Google’s Map Maker) road data in conjunction with population data in and around Nairobi, Kenya. Results show variability in coverage between all of these datasets. RCMRD provided the most complete, albeit less current, coverage when taking into account the entire study area, while OSM and Map Maker showed a degradation of coverage as one moves from central Nairobi towards rural areas. Furthermore, OSM had higher content density in large slums, surpassing the authoritative datasets at these locations, while Map Maker showed better coverage in rural housing areas. These results suggest a greater need for a more inclusive approach using VGI to supplement gaps in authoritative data in developing nations.
Highlights
Web 2.0 and the increased availability of relatively low cost location-aware mobile devices over the last decade have led to enormous amounts of user-generated geographical content online
This is because OSM and Map Maker coverage are very similar in this part of the study area, with roads from Map Maker being overshadowed by OSM roads
Moving away from Central Nairobi, it can be seen that there is a greater variability in coverage between road networks, with Kajiado and Machakos having a much higher presence of RCMRD coverage
Summary
Web 2.0 and the increased availability of relatively low cost location-aware mobile devices over the last decade have led to enormous amounts of user-generated geographical content online Sources of such user-generated information include wikis, blogs, social media feeds, such as Twitter and Flickr, and open web mapping platforms, such as OpenStreetMap (OSM) [1]. It can be used to supplement existing geographical layers, such as remote sensing imagery for improving the mapping of floods (e.g., [2]), or to provide a new lens through which to better understand people, communities and their interaction with their surroundings (e.g., [3]) This user-generated content is broadly referred to as volunteered geographic information (VGI, [4]), while additional terms, such as ambient geographical information (AGI, [5]), have been used to make the distinction between explicitly and implicitly crowd-contributed geographic content. Given the growing number of OSM users and the use of these data, it is expected that the number of applications using OSM will continue to grow in the foreseeable future
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