1. VIIRS Nighttime Lights Creating the Next Generation of Global Remotely-Sensed Nighttime Lights Products From VIIRS Day/Night Band (DNB) Data Chris Elvidge Earth Observation Group (EOG) NOAA National Centers for Environmental Information (NCEI), USA chris.elvidge@noaa.gov Kimberly Baugh, Mikhail Zhizhin, Feng-Chi Hsu, Tilottama Ghosh CIRES - University of Colorado, USA

2. Nighttime Lights Composites (Historical OLS Products) The EOG Group at NCEI has a long history of making global annual nighttime lights composite products using DMSP-OLS data. http://www.ngdc.noaa.gov/eog/dmsp/downloadV4composites.html

3. VIIRS Day-Night Band vs DMSP-OLS Quantization: DNB is 14 bit versus 6 bit for OLS. Dynamic Range: Due to limited dynamic range, OLS data saturate on bright lights in operational data collections. Lower Detection Limits: DNB can detect dimmer lighting than OLS. Quantitative: DNB is calibrated, the OLS visible band has no in-flight calibration. Multispectral: VIIRS has additional spectral bands to discriminate combustion sources from lights and to characterize the optical thickness of clouds.

4. VIIRS Nighttime Lights Composite – 2015/01 Still has aurora, fires and background noise

5. VIIRS Nighttime Lights Composite October 2014 Hong Kong

6. Current Status A time series of 18 monthly DNB cloud-free composites are available at: http://www.ngdc.noaa.gov/eog/viirs/download_monthly.html Core algorithms have been developed for filtering of: Lightning Fires Blurry lights Background noise 18,000+ gas flares have been identified using IR channel data (Nightfire). In the coming months we will work on producing a clean nighttime lights product for 2015

7. Applications for VIIRS Nighttime Lights Spatial definition of human settlements and areas with built infrastructure Measuring growth rates in built infrastructure Spatial extent of electrification Power grid stability analyses Power outage detection Estimating the density of constructed surfaces Modeling habitat fragmentation Light pollution studies Spatial modeling of economic indices Gridded GDP Poverty mapping Urban metabolism analyses Spatial modeling of fossil fuel carbon emissions, water consumption, waste water production, … 7 All of these applications work best with a cleaned NTL product, with fires, flares & noise removed