Research on Light Pollution Issues based on Airborne Radar Point Cloud Data

Abstract

It is of extensive significance to evaluate the risk degree of light pollution and prevent the harm of light pollution. In this paper, 149 airborne radar point cloud data were processed by Southlidar software, and the point cloud data were processed by progressive morphological filtering function, and seven geographic information indexes were formed, including green coverage, ground area percentage, construction area percentage, water body area percentage, and road area percentage, and the relationship between them and the risk factors affecting light pollution was found. Then, according to the seven indicators, the classification basis of light pollution risk level based on entropy weight-fuzzy comprehensive evaluation model was established, and the light pollution risk level was divided into I. to IV levels according to the evaluation results. Secondly, the linear discriminant analysis model is used to establish the canonical discriminant function to judge the risk degree of the sample data of City, Suburban, Countryside and protected areas.