Publicação
Illuminating Inequality
| Resumo: | Artificial light pollution at night (ALAN) poses significant environmental and social challenges, impacting biodiversity, human health, and energy efficiency. This study examines the spatial distribution of ALAN across England and its relationship with population density, income, and Index of Multiple Deprivation (IMD). Using 2022 VIIRS data, Moran’s I, Ordinary Least Squares (OLS), and Geographically Weighted Regression (GWR) were applied to assess these relationships. GWR outperformed OLS, capturing spatial heterogeneity and revealing localized associations. Population density emerged as the strongest predictor, particularly in urban areas, while income was a key factor in affluent southern regions. Elevated ALAN in deprived areas suggest the influence of additional factors like land use and infrastructure. These findings underscore the need for localized lighting strategies to address environmental and social disparities and promote sustainable urban planning. |
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| Autores principais: | Neri, Margaux |
| Outros Autores: | Tang, Vicente |
| Assunto: | light pollution inequality England spatial statistics SDG 10 - Reduced Inequalities SDG 11 - Sustainable Cities and Communities SDG 3 - Good Health and Well-being SDG 7 - Affordable and Clean Energy SDG 15 - Life on Land |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | póster em conferência |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | Artificial light pollution at night (ALAN) poses significant environmental and social challenges, impacting biodiversity, human health, and energy efficiency. This study examines the spatial distribution of ALAN across England and its relationship with population density, income, and Index of Multiple Deprivation (IMD). Using 2022 VIIRS data, Moran’s I, Ordinary Least Squares (OLS), and Geographically Weighted Regression (GWR) were applied to assess these relationships. GWR outperformed OLS, capturing spatial heterogeneity and revealing localized associations. Population density emerged as the strongest predictor, particularly in urban areas, while income was a key factor in affluent southern regions. Elevated ALAN in deprived areas suggest the influence of additional factors like land use and infrastructure. These findings underscore the need for localized lighting strategies to address environmental and social disparities and promote sustainable urban planning. |
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