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Natural Cities Generated from All Building Locations in America

Author

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  • Bin Jiang

    (Faculty of Engineering and Sustainable Development, Division of GIScience, University of Gävle, SE-801 76 Gävle, Sweden)

Abstract

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.

Suggested Citation

  • Bin Jiang, 2019. "Natural Cities Generated from All Building Locations in America," Data, MDPI, vol. 4(2), pages 1-5, April.
    • Handle: RePEc:gam:jdataj:v:4:y:2019:i:2:p:59-:d:226999
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    References listed on IDEAS

    as
    1. Bin Jiang & Junjun Yin, 2014. "Ht-Index for Quantifying the Fractal or Scaling Structure of Geographic Features," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 104(3), pages 530-540, May.
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    Cited by:

    1. Hiroyuki Usui, 2023. "Cost-Efficient Urban Areas Minimising the Connection Costs of Buildings by Roads: Simultaneous Optimisation of Criteria for Building Interval and Built Cluster Size," Networks and Spatial Economics, Springer, vol. 23(1), pages 65-96, March.
    2. Dan Wang & Liang Kong & Zhongsheng Chen & Xia Yang & Mingliang Luo, 2022. "Physical Urban Area Identification Based on Geographical Data and Quantitative Attribution of Identification Threshold: A Case Study in Chongqing Municipality, Southwestern China," Land, MDPI, vol. 12(1), pages 1-18, December.

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