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

  • Samuel Lee ToepkeEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (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.

Keywords

Population estimation Structure occupancy curve Social media Geofencing Enterprise architecture Volunteered geographic data 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Private Engineering FirmWashington DCUSA

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