An Assessment of the Accuracy of Volunteered Road Map Production in Western Kenya

Abstract

Abstract:The introduction of web based mapping facilities that use satellite imagery, offers local people the possibility to map their environment. However, maps need to be accurate, which is the reason why map making is assigned to professionals. In this paper, we investigated the classification accuracy of road infrastructure from high resolution satellite imagery of an urban area in western Kenya achieved by surveyors and non-surveyors alike, with and without local knowledge. Those with local knowledge classified roads with over 92% accuracy on average, irrespective of surveying background. Professional surveyors and laymen without local knowledge achieved lower accuracies of 67.7% and 42.9% respectively. We argue that local knowledge is also likely to improve the classification accuracy of many other attributes featured in topographic maps and thus conclude that there is reason to consider engaging local expertise in the production and updating of topographic maps.

Authoritative and Volunteered Geographical Information in a Developing Country: A Comparative Case Study of Road Datasets in Nairobi, Kenya

“…For example, work by Leeuw et al [90] in western Kenya showed that local knowledge plays an important role in improving the accuracy of VGI contributions. In that study, participants with local knowledge, on average, were able to classify roads with over 92% accuracy, compared to professional surveyors (67.7%) and other laymen users without local knowledge of the area (42.9%).…”

Local Knowledge and Professional Background Have a Minimal Impact on Volunteer Citizen Science Performance in a Land-Cover Classification Task

“…Yet location and local knowledge have been found to be relevant in studies of other types of tasks. A comparison of the contributions of local volunteers in classifying road types from imagery with professional surveyors found that the accuracy increased from 68% to 92% when the data were collected by the local volunteers [33]. OpenStreetMap is built on the idea that local knowledge is of fundamental importance in contributing and tagging features [34] yet many humanitarian mapping exercises use remote mappers to provide rapid information for response teams.…”

Intelligence and Information Gathering Through Deliberative Crowdsourcing

“…Democratization in map making has the potential "to add to an old science by allowing anyone with access to a computer to upload their findings" (Valdes, 2013). De Leeuw et al (2011) find that the local knowledge that is aggregated via crowdsourcing actually had greater level accuracy than professional surveyors in urban areas of western Kenya. This finding provides support to the power of the crowd and the importance of local knowledge in many map-making endeavors.…”