Changes in outdoor lighting in Germany from 2012-2016

Abstract

Changes in the total lit area and the radiance of stably lit area in the German federal states from 2012-2016 were investigated using satellite observations from 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 most rapidly, but it is possible that their large increases are to some extent driven by a darker than usual observation in 2012. Thüringen was dramatically different from the other states, with an annual decrease in lit area, and in the radiance of stably lit areas. The rates of change measured from 2012-2015 and 2013-2016 are strongly correlated with each other (Pearson's ρ=0.67, p=0.01). In most states, least squares fits for the rate of change match the rate calculated as a ratio of 2016 to 2012. These results are therefore consistent with the hypothesis that the changes in observed radiance are due to lighting change, but this should be verified in the future when longer time series are available. Due to the (500-900 nm) spectral response of the satellite, transitions from high pressure sodium to LED street lighting that preserve total lumen output are be expected to be observed as a decrease in radiance. Since such decreases are not observed in most states, the observations of increasing light emissions in most states are not indicative of a national transition toward sustainable lighting. In addition to these results, this paper discusses the role of remotely sensed nighttime data within the context of sustainable lighting.

Multi-Level Relationships between Satellite-Derived Nighttime Lighting Signals and Social Media–Derived Human Population Dynamics

“…Human settlements located in different areas might demonstrate varying characteristics resulting from underlying differences in urbanization. In addition, it is noteworthy that seasonal and monthly variations in both social media-derived human activity and VIIRS DNB nighttime light signals [34], and other driving factors for instance, cultural and demographic differences and the lighting technology [44][45][46][47], could affect the quantitative relationship between NTL and NLR and should be taken into account in future studies.…”

“…All these results jointly indicate a spatial disparity in the quantitative relationship between regional nighttime light signals and the corresponding degree of location requests; the variation gradually increases with the observation level from the provincial level to the county level, primarily due to the enhanced spatial independence of both variables. Additionally, It should be mentioned that although the observed degree of human activity in association with the effect of spatial autocorrelation can explain most major variations in nighttime lighting signals, other underlying driving factors, for example, cultural differences on street lighting [44] and its dynamics [45], inter-regional differences in demography [46], and various lighting technology uses [47], can also contribute the regional disparity in the relationship between NTL and Additionally, It should be mentioned that although the observed degree of human activity in association with the effect of spatial autocorrelation can explain most major variations in nighttime lighting signals, other underlying driving factors, for example, cultural differences on street lighting [44] and its dynamics [45], inter-regional differences in demography [46], and various lighting technology uses [47], can also contribute the regional disparity in the relationship between NTL and NLR at different observation levels. Thus, the quantitative response of nighttime lights to corresponding human activity might differ regionally with various demographic, socioeconomic, cultural, and technical factors, especially across a vast region like China.…”

Variation of Individual Location Radiance in VIIRS DNB Monthly Composite Images

“…On the other hand, when summing the light from smaller regions, such as an individual city, one must expect spatially correlated fluctuations, and therefore larger uncertainty on the observed radiance. An example of an extreme variation in a small area in a single monthly composite was recently reported for the city-state of Bremen in Germany [55]. These outliers would be of concern for studies that depend on time series in small areas, such as evaluating economic changes in individual cities (e.g.…”

“…One may therefore question whether previous studies of national and state level trends using DNB light emissions have drawn correct conclusions. For example, Kyba et al [55] examined 5-year time series of German federal states, and claimed to observe changes on the level of -7% to +40%. Are such reports correct?…”

Working with Inadequate Tools: Legislative Shortcomings in Protection against Ecological Effects of Artificial Light at Night

“…For example, nightscapes in Germany brightened in the years 2012-2016 similarly to the global trend. While the night sky brightness declined in a few federal states, such as Thuringia (−17%) and Saxony-Anhalt (−5.6%), it increased considerably in other federal states, such as Bavaria (+35%) and Hamburg (+29%) [18]. The development of efficient lighting solutions is thwarted by rebound effects [11,19].…”