Citizen Science Provides Valuable Data for Monitoring Global Night Sky Luminance

The skyglow produced by artificial lights at night is one of the most dramatic anthropogenic modifications of Earth’s biosphere. The GLOBE at Night citizen science project allows individual observers to quantify skyglow using star maps showing different levels of light pollution. We show that aggregated GLOBE at Night data depend strongly on artificial skyglow, and could be used to track lighting changes worldwide. Naked eye time series can be expected to be very stable, due to the slow pace of human eye evolution. The standard deviation of an individual GLOBE at Night observation is found to be 1.2 stellar magnitudes. Zenith skyglow estimates from the ‘‘First World Atlas of Artificial Night Sky Brightness’’ are tested using a subset of the GLOBE at Night data. Although we find the World Atlas overestimates sky brightness in the very center of large cities, its predictions for Milky Way visibility are accurate

Worldwide variations in artificial skyglow

Despite constituting a widespread and significant environmental change, understanding of artificial nighttime skyglow is extremely limited. Until now, published monitoring studies have been local or regional in scope, and typically of short duration. In this first major international compilation of monitoring data we answer several key questions about skyglow properties. Skyglow is observed to vary over four orders of magnitude, a range hundreds of times larger than was the case before artificial light. Nearly all of the study sites were polluted by artificial light. A non-linear relationship is observed between the sky brightness on clear and overcast nights, with a change in behavior near the rural to urban landuse transition. Overcast skies ranged from a third darker to almost 18 times brighter than clear. Clear sky radiances estimated by the World Atlas of Artificial Night Sky Brightness were found to be overestimated by ~25%; our dataset will play an important role in the calibration and ground truthing of future skyglow models. Most of the brightly lit sites darkened as the night progressed, typically by ~5% per hour. The great variation in skyglow radiance observed from site-to-site and with changing meteorological conditions underlines the need for a long-term international monitoring program

Changes in outdoor lighting in Germany from 2012-2016

Changes in the total lit area and the radiance of stably lit area in the German federal states from 2012-2016 were investigated using the Day-Night Band of the Visible Infrared Imaging Radiometer Suite. Most states increased in both lit area and radiance. The lit area of Bayern and Schleswig-Holstein grew rapidly, at annual rates of 9.7% and 8.8% respectively. Thüringen was dramatically different from the other states, with a 4.5% annual decrease in lit area, and a 17% annual decrease in the radiance of stably lit areas. In at least some cases, the increases in lighting in Bayern area associated with transitions to LEDs, which may not be indicative of a transition towards sustainable lighting. In addition to these results, this paper discusses the role of remotely sensed nighttime data within the context of sustainable lighting

Reducing Variability and Removing Natural Light from Nighttime Satellite Imagery: A Case Study Using the VIIRS DNB

Temporal variation of natural light sources such as airglow limits the ability of night light sensors to detect changes in small sources of artificial light (such as villages). This study presents a method for correcting for this effect globally, using the satellite radiance detected from regions without artificial light emissions. We developed a routine to define an approximate grid of locations worldwide that do not have regular light emission. We apply this method with a 5 degree equally spaced global grid (total of 2016 individual locations), using data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB). This code could easily be adapted for other future global sensors. The correction reduces the standard deviation of data in the Earth Observation Group monthly DNB composites by almost a factor of two. The code and datasets presented here are available under an open license by GFZ Data Services, and are implemented in the Radiance Light Trends web application