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Natural Cities Generated from All Building Locations in America
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Geospatial Sciences.ORCID iD: 0000-0002-2337-2486
2019 (English)In: Data, ISSN 2306-5729, Vol. 4, no 2, article id 59Article in journal (Refereed) Published
Abstract [en]

Authorities define cities-or human settlements in general-through imposing top-down rules in terms of whether buildings belong to cities. Emerging geospatial big data makes it possible to define cities from the bottom up, i.e., buildings determine themselves whether they belong to a city using the notion of natural cities and based on head/tail breaks, which is a classification and visualization tool for data with a heavy-tailed distribution. In this paper, we used 125 million building locations-all building footprints of America (mainland) or their centroids more precisely-to generate 2.1 million natural cities in the country (see the URL as shown in the note of Figure 1). In contrast to government defined city boundaries, these natural cities constitute a valuable data source for city-related research.

Place, publisher, year, edition, pages
2019. Vol. 4, no 2, article id 59
Keywords [en]
head, tail breaks, natural cities, Zipf's law, geospatial big data
National Category
Civil Engineering
Identifiers
URN: urn:nbn:se:hig:diva-31076DOI: 10.3390/data4020059ISI: 000475303500013Scopus ID: 2-s2.0-85066427424OAI: oai:DiVA.org:hig-31076DiVA, id: diva2:1372995
Available from: 2019-11-26 Created: 2019-11-26 Last updated: 2019-11-26Bibliographically approved

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Jiang, Bin

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