A light pollution risk intervention strategy optimization model based on improved PCA clustering algorithm

Ruohong Yang, Jiahui Qiu, Ainuo Liu, Jianjia Wang*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

Abstract

Artificial light sources have a profound impact on the night sky, leading to reduced visibility of stars and contributing to light pollution. The environmental, physiological, and psychological consequences of light pollution are severe, including disrupting ecosystems, biological clocks, and endocrine imbalances in humans. Moreover, excessive lighting also wastes energy and exacerbates the energy crisis. This paper collects eight light pollution indicators and proposes a general measurement model for light pollution risk level using an improved PCA clustering algorithm. This paper also proposes intervention strategy optimization model to reduce the risk level, and evaluates the effectiveness of these interventions in Shanghai. Overall, this paper provides insights into the causes and consequences of light pollution, and practical solutions for mitigating its harmful effects.

Original languageEnglish
Title of host publicationThird International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2023
EditorsKannimuthu Subramaniam, Pavel Loskot
PublisherSPIE
ISBN (Electronic)9781510668522
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event3rd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2023 - Kuala Lumpur, Malaysia
Duration: 30 Jun 20232 Jul 2023

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12799
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference3rd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2023
Country/TerritoryMalaysia
CityKuala Lumpur
Period30/06/232/07/23

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