GC11B-1029
Estimating global per-capita carbon emissions with VIIRS nighttime lights satellite data

Monday, 14 December 2015
Poster Hall (Moscone South)
Tommy Jasmin1, Ankur R Desai1 and R. Bradley Pierce2, (1)University of Wisconsin Madison, Madison, WI, United States, (2)NOAA Camp Springs, Camp Springs, MD, United States
Abstract:
With the launch of the Suomi National Polar-orbiting Partnership (NPP) satellite in November 2011, we now have nighttime lights remote sensing capability vastly improved over the predecessor Defense Meteorological Satellite Program (DMSP), owing to improved spatial and radiometric resolution provided by the Visible Infrared Imaging Radiometer Suite (VIIRS) Day Night Band (DNB) along with technology improvements in data transfer, processing, and storage. This development opens doors for improving novel scientific applications utilizing remotely sensed low-level visible light, for purposes ranging from estimating population to inferring factors relating to economic development. For example, the success of future international agreements to reduce greenhouse gas emissions will be dependent on mechanisms to monitor remotely for compliance. Here, we discuss implementation and evaluation of the VRCE system (VIIRS Remote Carbon Estimates), developed at the University of Wisconsin-Madison, which provides monthly independent, unbiased estimates of per-capita carbon emissions. Cloud-free global composites of Earth nocturnal lighting are generated from VIIRS DNB at full spatial resolution (750 meter). A population equation is derived from a linear regression of DNB radiance sums at state level to U.S. Census data. CO2 emissions are derived from a linear regression of VIIRS DNB radiance sums to U.S. Department of Energy emission estimates. Regional coefficients for factors such as percentage of energy use from renewable sources are factored in, and together these equations are used to generate per-capita CO2 emission estimates at the country level.