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Mapping Refrigerant Gases in the New York City Skyline.
Sci Rep
June 2017
New York University, Center for Urban Science and Progress, Brooklyn, NY, USA.
Cities are now home to more than 50% of the world's population and emit large quantities of pollutants from sources such as fossil fuel combustion and the leakage of refrigerants. We demonstrate the utility of persistent synoptic longwave hyperspectral imaging to study the ongoing leakage of refrigerant gases in New York City, compounds that either deplete the stratosphere ozone or have significant global warming potential. In contrast to current monitoring programs that are based on country-level reporting or aggregate measures of emissions, we present the identification of gaseous plumes with high spatial and temporal granularity in real-time over the skyline of Manhattan.
View Article and Find Full Text PDFA Hyperspectral Survey of New York City Lighting Technology.
Sensors (Basel)
December 2016
NYU Center for Urban Science and Progress, 1 MetroTech Center, Brooklyn, NY 11201, USA.
Using side-facing observations of the New York City (NYC) skyline, we identify lighting technologies via spectral signatures measured with Visible and Near Infrared (VNIR) hyperspectral imaging. The instrument is a scanning, single slit spectrograph with 872 spectral channels from 0.4-1.
View Article and Find Full Text PDFUsing Big Data to Understand the Human Condition: The Kavli HUMAN Project.
Big Data
September 2015
New York University, New York, New York.
Until now, most large-scale studies of humans have either focused on very specific domains of inquiry or have relied on between-subjects approaches. While these previous studies have been invaluable for revealing important biological factors in cardiac health or social factors in retirement choices, no single repository contains anything like a complete record of the health, education, genetics, environmental, and lifestyle profiles of a large group of individuals at the within-subject level. This seems critical today because emerging evidence about the dynamic interplay between biology, behavior, and the environment point to a pressing need for just the kind of large-scale, long-term synoptic dataset that does not yet exist at the within-subject level.
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