Temporal and Spatial Analysis of Light Pollution Changes: A Case Study of Italy

This study presents a comprehensive temporal and spatial analysis of light pollution in Italy using the VIIRS-DNB dataset, the Mann–Kendall Trend Model (MKTM), the Sen's Slope Estimator (SSE) method, Bortle classes, and the QGIS-Molusce plugin. In the entire data set analyzed, an increasing Artificial Light (AL) trend is observed in 68 Italian provinces and a decreasing AL trend in 40 provinces. Examining the distribution of light pollution across the country for 2022, Ogliastra and Rome show the lowest and highest values, respectively. Light pollution strongly correlates with the number of inhabited households (Formula presented.) and. Gross National Product (GNP) (Formula presented.). Many observatories are strongly affected by AL. Furthermore, between 2012 and 2022, the darkest sky quality categories, namely “Excellent sky (> 21.9 (Formula presented.)), Typical dark sky (21.9–21.5 (Formula presented.)), and Rural sky (21.5–21.3 (Formula presented.))” have completely disappeared. As a result, the Annual Rate of Change Percentage (ARC%) has been calculated as −10. The analysis of the transition matrix shows that the combined classes (22.02–20.8 (Formula presented.)) are mostly converted to suburban areas (20.8–20.1 (Formula presented.)), and this conversion rate is quite high (90.14%). The results show statistically reliable findings that will help national and local governments to tackle the problems more effectively. © 2025 Wiley-VCH GmbH.