Potential of crowdsourced data for integrating landmarks and routes for rescue in mountain areas

ABSTRACT Many different websites offer the opportunity to share and download landmarks and routes produced by the crowd. Landmarks near to a route or routes passing near to some landmarks may help in the context of mountain rescue. Therefore, it is necessary to identify relevant data sources and to describe their characteristics. In this paper, we set out to explore the potential of crowdsourced data in order to be considered such as data sources in the context of mountain rescue. Thus, our aim is to study the content of different sources to have a better knowledge on how landmarks and routes are mapped, to demonstrate the complementarity of crowdsourced data with respect with authoritative data, and to study the feasibility of defining links between routes and landmarks. The proposed method used integration techniques such as map matching, route construction and data matching. Among the results, the large number of non-matched features proves the richness of crowdsourced data. The matching results generate new semantic rules for both type of landmarks and geometries of route.