A simplified model of all-sky artificial sky glow derived from VIIRS Day/Night band data. (July 2018)

• Record Type: Journal Article
• Authors: Duriscoe, Dan M.; Anderson, Sharolyn J.; Luginbuhl, Christian B.; Baugh, Kimberly E.
• Is Part Of: Journal of quantitative spectroscopy & radiative transfer. Volume 214(2018)
• Page Start: 133
• Page End: 145
• Publication Date: 2018-07
• Subjects: Night sky brightness -- Light pollution -- Landscape scale assessments; Spectrum analysis -- Periodicals; Radiation -- Periodicals; Analyse spectrale -- Périodiques; Rayonnement -- Périodiques; Radiation; Spectrum analysis; Periodicals; 543.0858
• DOI: 10.1016/j.jqsrt.2018.04.028
• Languages: English
• ISSNs: 0022-4073

Abstract

Highlights: A simplified spatial model provides a high confidence estimate of an all-sky light pollution ratio (ALR) metric for large regions. The model uses VIIRS Day/Night band cloud-free composites as input and is verified with ground-based all-sky V-band photometric artificial sky brightness measurements. The simplified algorithm is based upon an all-sky brightness/distance relationship between the location of the observer and the source of upward radiance. We provide limitations of the model including the effect of sources of varying spectral power distribution and the appearance of artificial sky glow to the human eye. Abstract: We present a simplified method using geographic analysis tools to predict the average artificial luminance over the hemisphere of the night sky, expressed as a ratio to the natural condition. The VIIRS Day/Night Band upward radiance data from the Suomi NPP orbiting satellite was used for input to the model. The method is based upon a relation between sky glow brightness and the distance from the observer to the source of upward radiance. This relationship was developed using a Garstang radiative transfer model with Day/Night Band data as input, then refined and calibrated with ground-based all-sky V-band photometric data taken under cloudless and low atmospheric aerosol conditions. An excellent correlation was found between observed sky quality and the predicted values from the remotely sensed data. Thematic maps of large regions of the earth showing predicted artificial V-band sky brightness may be quickly generated with modest computing resources. We have found a fast and accurate method based on previous work to model all-sky quality. We provide limitations to this method. The proposed model meets requirements needed by decision makers and land managers of an easy to interpret and understand metric of sky quality.