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Investigation of Geospatially Enabled, Social Media Generated Structure Occupancy Curves in Commercial Structures

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Geographical Information Systems Theory, Applications and Management (GISTAM 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 741))

Abstract

Spatiotemporal human-use estimations, via occupancy curves of a high-traffic commercial structure, have been shown to be attainable using publicly available social media data. The data is crowd sourced, geospatially enabled, and gathered from open web services using a commercially available, enterprise cloud architecture. After data processing, an interested individual can view a graph displaying population over a twenty four hour period for a specific building, with this work focusing on several structures in downtown San Jose, CA, USA. New structure data is explored to bolster previous findings, structure curves are compared to Google Popular Times charts, and further discussion includes limitations of this method and the benefit of error estimation.

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Author information

Authors and Affiliations

  1. Private Engineering Firm, Washington DC, USA

    Samuel Lee Toepke

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  1. Samuel Lee Toepke
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Correspondence to Samuel Lee Toepke .

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Editors and Affiliations

  1. Polytechnic Institute of Setúbal/IPS, Setúbal, Portugal

    Cédric Grueau

  2. INSA Lyon, University of Lyon, Villeurbanne Cedex, France

    Robert Laurini

  3. Departamento de Informatica, Universidade do Minho, Braga, Portugal

    Jorge Gustavo Rocha

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Toepke, S.L. (2017). Investigation of Geospatially Enabled, Social Media Generated Structure Occupancy Curves in Commercial Structures. In: Grueau, C., Laurini, R., Rocha, J. (eds) Geographical Information Systems Theory, Applications and Management. GISTAM 2016. Communications in Computer and Information Science, vol 741. Springer, Cham. https://doi.org/10.1007/978-3-319-62618-5_4

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  • DOI: https://doi.org/10.1007/978-3-319-62618-5_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62617-8

  • Online ISBN: 978-3-319-62618-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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