Dynamics of the urban lightscape. (December 2015)

• Record Type: Journal Article
• Authors: Dobler, Gregory; Ghandehari, Masoud; Koonin, Steven E.; Nazari, Rouzbeh; Patrinos, Aristides; Sharma, Mohit S.; Tafvizi, Arya; Vo, Huy T.; Wurtele, Jonathan S.
• Is Part Of: Information systems. Volume 54(2015)
• Page Start: 115
• Page End: 126
• Publication Date: 2015-12
• Subjects: Urban imaging -- Visible light observations -- Time series -- Image processing -- Pattern recognition; Database management -- Periodicals; Electronic data processing -- Periodicals; Bases de données -- Gestion -- Périodiques; Informatique -- Périodiques; Database management; Electronic data processing; Periodicals; 005.7
• DOI: 10.1016/j.is.2015.06.002
• Languages: English
• ISSNs: 0306-4379

Abstract

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.