Quantitative Assessment of Light Pollution: A Study on Index Construction Based on Entropy Weight and Topsis Methods

Junyi Yang; Song Zeng; Jiahao Yang; Yutong Wu; Zhengguo Yang

doi:10.54097/fmb8kc79

Authors

Junyi Yang
Song Zeng
Jiahao Yang
Yutong Wu
Zhengguo Yang

DOI:

https://doi.org/10.54097/fmb8kc79

Keywords:

Light pollution index, Entropy weight method, Topsis, comprehensive evaluation model, K-means + +.

Abstract

In recent years, the awareness of light pollution's hazards has grown. This article aims to develop metrics to assess light pollution, propose intervention strategies, and analyze their effectiveness. Key indicators such as population density, GDP, urban electricity consumption, high-rise buildings, vehicle ownership rate, AOD index, and remote sensing brightness were evaluated. Using entropy weight and Topsis methods, a Light Pollution Index (LPI) was derived. A multivariate regression model provided the regression equation for LPI. K-means++ clustering categorized LPI into five levels, delineating light pollution degrees in different regions. This framework aids urban planning assessments and establishes a comprehensive model for light pollution assessment. Through data analysis and evaluation, the feasibility of light pollution reduction measures was demonstrated.

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