Abstract

Central Place Theory explains the number and locations of cities, towns, and villages based on principles of market areas, transportation, and socio-political interactions between settlements. It assumes a hexagonal segmentation of space, where every central place is surrounded by six lower-order settlements in its range, to which it caters its goods and services. In reality, this ideal hexagonal model is often skewed based on varying population densities, locations of natural features and resources, and other factors. In this paper, we propose an approach that extracts the structure around a central place and its range from the link structure on the Web. Using a corpus of georeferenced documents from the English language edition of Wikipedia, we combine weighted links between places and semantic annotations to compute the convex hull of a central place, marking its range. We compare the results obtained to the structures predicted by Central Place Theory, demonstrating that the Web and its hyperlink structure can indeed be used to infer spatial structures in the real world. We demonstrate our approach for the four largest metropolitan areas in the United States, namely New York City, Los Angeles, Chicago, and Houston.