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Rethinking Spatial Tessellation in an Era of the Smart City

Author

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  • Jin Xing
  • Renee Sieber
  • Stéphane Roche

Abstract

Smart cities frequently rely on vast sensor networks, such as traffic cameras and ventilation controllers. This requires that we rethink methods of spatial tessellation. As tessellation is becoming more dynamic, we often combine multiple tessellation methods and switch tessellation shapes frequently for different data collection and analytics. In this article, we review how tessellation works with the object and field geographic spatial models. To achieve the “smartness” within cities, this article introduces the dynamic tessellation approach as the initial solution. Key Words: big data, sensor network, smart city, spatial tessellation.

Suggested Citation

  • Jin Xing & Renee Sieber & Stéphane Roche, 2020. "Rethinking Spatial Tessellation in an Era of the Smart City," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 110(2), pages 399-407, March.
    • Handle: RePEc:taf:raagxx:v:110:y:2020:i:2:p:399-407
    DOI: 10.1080/24694452.2019.1662766
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    Cited by:

    1. Hagen, Tobias & Hamann, Jonas & Saki, Siavash, 2022. "Discretization of urban areas using POI-based tesselation," Working Paper Series 23, Frankfurt University of Applied Sciences, Faculty of Business and Law.

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