Light Pollution Evaluation Research Based on the Entropy Weight Method Combined with the TOPSIS Model

Abstract

Light pollution has emerged as a significant environmental issue, joining the ranks of other pollutants such as waste gas and wastewater in posing serious threats to environmental safety and public health. Unlike traditional pollutants, light pollution is often less visible in regulatory frameworks, yet its effects on ecosystems, human health, and overall environmental quality are profound and increasingly recognized. As urbanization expands and artificial lighting becomes more prevalent, the need to accurately measure and mitigate the impacts of light pollution becomes ever more critical. To tackle the complexities associated with assessing light pollution across diverse geographical locations, this paper introduces a comprehensive and versatile evaluation model. The proposed model integrates the TOPSIS method, enhanced by the entropy weight method, and is further supported by multiple regression analysis and random forest algorithms. Together, these methodologies form a robust framework for quantifying light pollution risk levels across various environments. By providing a systematic approach to light pollution assessment, this research offers valuable insights for the development of global light pollution evaluation systems. Furthermore, the findings contribute to the broader discourse on effective management strategies, offering a reference point for policymakers and researchers involved in environmental protection and sustainable urban planning.