Abstract
When human beings enjoy the prosperity of the city, it is difficult to escape the ubiquitous light pollution. In order to develop a widely applicable metric to determine the level of light pollution risk, the article establishes a light pollution risk level identification model. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is adopted for comprehensive evaluation of 4 types of light pollution. In order to improve the weight assignment process of TOPSIS, the entropy weight method (EWM) is used. Finally, the article conducts K-Means clustering algorithm to grade the risk level of different locations. The proportion of regions of high risk, medium risk and low risk are 28.57%, 42.86% and 28.57% respectively.
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