Quantitative supervised learning system of light pollution and its application

Light pollution is a new, invisible form of pollution that poses a threat to the health of humans and other species without awareness. Therefore, it is necessary to quantify the risk of light pollution, increase public awareness, and develop effective intervention strategies. This paper establishes a three-layer light pollution risk quantification system (P-S-N: light pollution risk- macro index-specific index). The players represent the light pollution risk index, the S-layers reflect its different dimensions, and the N-layers represent specific features. By inputting relevant index data in the N layer, the light pollution risk index of the P layer can be calculated.