Citizen Science to Assess Light Pollution with Mobile Phones

Abstract

The analysis of the colour of artificial lights at night has an impact on diverse fields, but current data sources have either limited resolution or scarce availability of images for a specific region. In this work, we propose crowdsourced photos of streetlights as an alternative data source: for this, we designed NightUp Castelldefels, a pilot for a citizen science experiment aimed at collecting data about the colour of streetlights. In particular, we extract the colour from the collected images and compare it to an official database, showing that it is possible to classify streetlights according to their colour from photos taken by untrained citizens with their own smartphones. We also compare our findings to the results obtained from one of the current sources for this kind of study. The comparison highlights how the two approaches give complementary information about artificial lights at night in the area. This work opens a new avenue in the study of the colour of artificial lights at night with the possibility of accurate, massive and cheap data collection.

Light pollution evaluation system based on combination weighting method

“…Strategy Three: Develop strategies to reduce light pollution risk levels in terms of coverage for biodiversity. Implementation case: optimize light color to enrich biodiversity [17]; reduce the use of artificial lights in vegetation [18]; improve green coverage; comply with the Bonn Convention [19]; create environmental protection areas and reduce the use of artificial light sources. The collected data from China and the United States are tested using a quasi-exponential law, and the test results are shown in 0.…”