Document Type

Article

Version Deposited

Published Version

Publication Date

12-1-2015

Publication Title

Information Systems

DOI

10.1016/j.is.2015.06.002

Abstract

The manifest importance of cities and the advent of novel data about them are stimulating interest in both basic and applied “urban science” (Bettencourt et al., 2007 [4]; Bettencourt, 2013 [3]). A central task in this emerging field is to document and understand the “pulse of the city” in its diverse manifestations (e.g., in mobility, energy use, communications, economics) both to define the normal state against which anomalies can be judged and to understand how macroscopic city observables emerge from the aggregate behavior of many individuals (Louail, 2013 [9]; Ferreira et al., 2013 [6]). Here we quantify the dynamics of an urban lightscape through the novel modality of persistent synoptic observations from an urban vantage point. Established astronomical techniques are applied to visible light images captured at 0.1 Hz to extract and analyze the light curves of 4147 sources in an urban scene over a period of 3 weeks. We find that both residential and commercial sources in our scene exhibit recurring aggregate patterns, while the individual sources decorrelate by an average of one hour after only one night. These highly granular, stand-off observations of aggregate human behavior – which do not require surveys, in situ monitors, or other intrusive methodologies – have a direct relationship to average and dynamic energy usage, lighting technology, and the impacts of light pollution. They may also be used indirectly to address questions in urban operations as well as behavioral and health science. Our methodology can be extended to other remote sensing modalities and, when combined with correlative data, can yield new insights into cities and their inhabitants.

Comments

This is an Open Access article published by Elsevier with a Creative Commons license.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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