Analyzing the obstruction effects of obstacles on light pollution caused by street lighting system in Cambridge, Massachusetts

Abstract

Artificial light has transformed urban life, enhancing visibility, aesthetics, and increasing safety in public areas. However, too much unwanted artificial light leads to light pollution, which has a negative effect on public health and urban ecosystems, as well as on the aesthetic and cultural meanings of the night sky. Some of the factors interfering with the estimation of light pollution in cities are urban features, such as the presence of trees, road dimensions, and the physical characteristics of buildings. In this study, we proposed a simplified model for unwanted upward light coming from street luminaires based on a building height model and the publicly accessible Google Street View images. We simulated and analyzed the obstruction effects of different street features on the light pollution caused by the street lighting system in Cambridge, Massachusetts. By providing quantitative information about the connections between the streetscape features and the amount of unwanted upward artificial light, this study provides reference values to inform policies aimed at curbing light pollution.

Direct measurement of the contribution of street lighting to satellite observations of nighttime light emissions from urban areas

“…This will include, for example, examining how obstacles block upward light emissions and quantifying how much urban light is emitted at angles too close to the horizon for satellites to observe. 3,39,42,43,58,59 A major challenge for this research will be to account for the variety in city morphology and lighting practice worldwide. As 'smart city' systems become increasingly common, they will allow similar city-scale experiments to address these and other questions related to the urban environment.…”

“…Consider that in cities with tall objects such as buildings or trees, the view of streetlights from space can be blocked. 22,42 Such blocking would decrease the value of s , and this would invalidate the prediction in those areas. Furthermore, streetlights are responsible for only a portion of emissions, and other applications (e.g.…”

“…38 In areas with tall buildings and trees, the view of the street level is partially or totally obscured. Improving understanding of the angular distribution of emissions from cities is an active field of research 3,[39][40][41][42][43][44] and remains one of the most important open questions in remote sensing of night lights and simulations of sky brightness. Finally, temporal factors also affect the radiance viewed from space.…”

Remote sensing of night lights: A review and an outlook for the future

“…In a recent paper, Li et al (2019b), have confirmed that the viewing angle of VIIRS/DNB affects the amount of measured night-time brightness, and that building height should be incorporated to understand the relationship between the satellite viewing zenith angle and emitted night-time lights. A different group (Li et al 2019c) have approached the problem from the other direction, using ground based all-sky imagery from Google Street View to examine how much light can escape to space, and how this is affected by changes in vegetation. Future research is required to extract this invaluable information from both DMSP/OLS and Suomi NPP/VIIRS DNB, and to remove angular effects from night-time products.…”

Life between buildings from a street view image: What do big data analytics reveal about neighbourhood organisational vitality?

“…More recently, Ibrahim et al (2020) reviewed how different deep learning methods can be applied to understand the built environment, noting a surging number of works that classify and segment GSV automatically into several built environment categories. Furthermore, it has been shown how built environment components derived from street-level images enable quantification of human perception of streets (Naik et al, 2016), the visual quality of cities (Ye et al, 2019), the level of light pollution (Li et al, 2019) and the pedestrian-related built environment (Aghaabbasi et al, 2018).…”