Abstract
Commuters have had an important role in shaping the spatial organization of Switzerland, as commuter flows have been one of the most significant criteria to delineate urban agglomeration zones. Even though urban areas and respective agglomerations have continuously gained in importance in Switzerland to this day, the Swiss national population census will no longer include commuter data at high spatial resolution. Hence, the definition of the rapidly evolving urban agglomeration concept will have to be modified for future urban research and planning purposes.We propose a crowdsourcing approach to overcome this data gap, and employ the open and web-based Wikipedia encyclopedia as a new resource to delineate agglomeration areas. Using the North Eastern parts of Switzerland in this case study, we systematically evaluate whether user-generated content can serve as an option to fill the commuter data gap in future Swiss national population censuses to define agglomeration areas. In a second step, we evaluate the influence of potential edge effects on our chosen approach.We employ the number of hyperlinks in the Wikipedia database to quantify the strength of functional relationships between municipalities appearing in the Wikipedia encyclopedia. Next, we visualize the extracted municipality network structure for the chosen study area. Finally, we cluster the connected municipalities to agglomeration zones, and compare the computed municipality clusters with the agglomeration areas currently defined by the Swiss census.Our results suggest that the aggregation structure of our crowdsourcing approach is congruent with the officially developed agglomeration areas proposed by the Swiss census. Crowdsourced data thus might be an additional future data resource to complement more traditional census statistics for space districting purposes or socio-economic research in urban geography and planning.However, our results also suggest that geographic space indeed influences even non-spatially organized, crowdsourced encyclopedic entries, and this must be systematically studied further in future studies.English Title: Agglomerations newly defined with crowdsourced data: visualizing North Eastern Switzerland based on Wikipedia content.
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