High-Resolution Imagery of Earth at Night: New Sources, Opportunities and Challenges

Images of the Earth at night are an exceptional source of human geographical data, because artificial light highlights human activity in a way that daytime scenes do not. The quality of such imagery dramatically improved in 2012 with two new spaceborne detectors. The higher resolution and precision of the data considerably expands the scope of possible applications. In this paper, we introduce the two new data sources and discuss their potential limitations using three case studies. Data from the Visible Infrared Imaging Radiometer Suite Day-Night Band (VIIRS DNB) is shown to have sufficient resolution to identify major sources of waste light, such as airports, and we find considerable variation in the peak radiance of the world's largest airports. Nighttime imagery brings "cultural footprints" to light: DNB data reveals that American cities emit many times more light per capita than German cities and that cities in the former East of Germany emit more light per capita than those in the former West. Photographs from the International Space Station, the second new source of imagery, provide some limited spectral information, as well as street-level resolution. These images may be of greater use for epidemiological studies than the lower resolution DNB data.

[1]  Franz Hölker,et al.  Two camera system for measurement of urban uplight angular distribution , 2013 .

[2]  Fachbereich Geowissenschaften von Städten des neuen Satelliten Suomi NPP , 2014 .

[3]  Birgit Glorius,et al.  Go west : internal migration in Germany after reunification , 2010 .

[4]  Christopher D. Elvidge,et al.  The Lumen Gini Coefficient: a satellite imagery derived human development index , 2012 .

[5]  Dar A. Roberts,et al.  A Comparison of Nighttime Satellite Imagery and Population Density for the Continental United States , 1997 .

[6]  Italy,et al.  The propagation of light pollution in the atmosphere , 2012, 1209.2031.

[7]  Alejandro Sánchez de Miguel,et al.  ISS nocturnal images as a scientific tool against Light Pollution: Flux calibration and colors , 2011 .

[8]  Jinliang Huang,et al.  Monitoring Trends in Light Pollution in China Based on Nighttime Satellite Imagery , 2014, Remote. Sens..

[9]  Travis Longcore,et al.  Ecological consequences of artificial night lighting , 2006 .

[10]  Stefanie Garz Erste Untersuchungen der Nachtaufnahmen von Städten des neuen Satelliten Suomi NPP , 2014 .

[11]  Stephen P. Mills,et al.  Suomi satellite brings to light a unique frontier of nighttime environmental sensing capabilities , 2012, Proceedings of the National Academy of Sciences.

[12]  Michael E. Coltrin,et al.  Solid-state lighting: an energy-economics perspective , 2010 .

[13]  K. Shadan,et al.  Available online: , 2012 .

[14]  I. Kloog,et al.  Light at Night Co‐distributes with Incident Breast but not Lung Cancer in the Female Population of Israel , 2008, Chronobiology international.

[15]  Christian B. Luginbuhl Using DMSP Night-Time Imagery to Evaluate Lighting Practice in the American Southwest , 2001 .

[16]  Alejandro Sánchez de Miguel,et al.  Image classification of night time images detected from the International Space Station , 2014 .

[17]  Till Roenneberg,et al.  IS LIGHT-AT-NIGHT A HEALTH RISK FACTOR OR A HEALTH RISK PREDICTOR? , 2009, Chronobiology international.

[18]  B. Griefahn,et al.  The Dark Side of Light: A Transdisciplinary Research Agenda for Light Pollution Policy , 2010 .

[19]  Boulder,et al.  The first World Atlas of the artificial night sky brightness , 2001, astro-ph/0108052.

[20]  Reed Olsen,et al.  Modelling US light pollution , 2014 .

[21]  Stuart R. Phinn,et al.  A new source for high spatial resolution night time images — The EROS-B commercial satellite , 2014 .

[22]  P. Sutton,et al.  Building and Evaluating Models to Estimate Ambient Population Density , 2003 .

[23]  Bruce G. Terrell,et al.  National Oceanic and Atmospheric Administration , 2020, Federal Regulatory Guide.

[24]  P. Sutton,et al.  Shedding Light on the Global Distribution of Economic Activity , 2010 .

[25]  P. Heilig,et al.  Light pollution , 2010, Spektrum der Augenheilkunde.

[26]  Christopher D. Elvidge,et al.  City lights and urban air , 2011 .

[27]  Steven D. Miller,et al.  Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band , 2013, Remote. Sens..

[28]  C. Elvidge,et al.  Citizen Science Provides Valuable Data for Monitoring Global Night Sky Luminance , 2013, Scientific Reports.

[29]  Juergen Fischer,et al.  Red is the new black: how the colour of urban skyglow varies with cloud cover , 2012 .

[30]  Noam Levin,et al.  High spatial resolution night-time light images for demographic and socio-economic studies , 2012 .

[31]  Miroslav Kocifaj,et al.  Using two light-pollution models to investigate artificial sky radiances at Canary Islands observatories , 2012 .

[32]  Caroline Geck,et al.  The World Factbook , 2017 .

[33]  D. Roberts,et al.  Census from Heaven: An estimate of the global human population using night-time satellite imagery , 2001 .

[34]  Michael G. Gartley,et al.  Using GIS databases for simulated nightlight imagery , 2012 .

[35]  J. Muller,et al.  Mapping regional economic activity from night-time light satellite imagery , 2006 .

[36]  C. Elvidge,et al.  Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption , 1997 .

[37]  Christopher C. M. Kyba,et al.  Redefining efficiency for outdoor lighting , 2014 .

[38]  Christian Wolter,et al.  Aerial survey and spatial analysis of sources of light pollution in Berlin, Germany , 2012 .

[39]  C. P. Lo Modeling the population of China using DMSP operational linescan system nighttime data , 2001 .

[40]  C. Elvidge,et al.  Limiting the impact of light pollution on human health, environment and stellar visibility. , 2011, Journal of environmental management.

[41]  Naizhuo Zhao,et al.  Mapping spatio-temporal changes of Chinese electric power consumption using night-time imagery , 2012 .

[42]  Christopher D. Elvidge,et al.  Spectral Identification of Lighting Type and Character , 2010, Sensors.

[43]  Christian B. Luginbuhl,et al.  From the Ground Up II: Sky Glow and Near-Ground Artificial Light Propagation in Flagstaff, Arizona , 2009 .

[44]  Jaime Zamorano,et al.  Atlas of astronaut photos of Earth at night , 2014 .

[45]  Yang Yang,et al.  Application of DMSP/OLS Nighttime Light Images: A Meta-Analysis and a Systematic Literature Review , 2014, Remote. Sens..

[46]  K. Gaston,et al.  Contrasting trends in light pollution across Europe based on satellite observed night time lights , 2014, Scientific Reports.

[47]  F. C. Bertiau,et al.  The artificial night-sky illumination in Italy. , 1973 .

[48]  Budhendra L. Bhaduri,et al.  A global poverty map derived from satellite data , 2009, Comput. Geosci..

[49]  Christopher D. F. Rogers,et al.  Mapping Lightscapes: Spatial Patterning of Artificial Lighting in an Urban Landscape , 2013, PloS one.

[50]  Mikhail Zhizhin,et al.  A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data , 2009 .

[51]  Alejandro Sánchez de Miguel Variación del brillo del fondo de cielo en el cénit con la fase y altura de la Luna , 2012 .

[52]  Jaime Zamorano,et al.  Evolution of the energy consumed by street lighting in Spain estimated with DMSP-OLS data , 2013, 1311.6992.

[53]  Christian Wolter,et al.  Light pollution as a biodiversity threat. , 2010, Trends in ecology & evolution.

[54]  C. Mandil Light's labour's lost : policies for energy-efficient lighting , 2006 .

[55]  S. Lewandowsky PLOS ONE 2013 , 2015 .

[56]  Paul D. Gamlin,et al.  Measuring and using light in the melanopsin age , 2014, Trends in Neurosciences.