Spatiotemporal Monitoring of Nighttime Light Satellite Data Using Google Earth Engine: Insights from the Italian Case

Nighttime light (NTL) satellite data provide an effective proxy for analyzing urbanization, tourism development, industrial activity, and population dynamics. Based on these premises, the present study investigates the spatiotemporal behavior of Nighttime Light Dynamics across 107 Italian provinces from 2014 to 2022 using VIIRS Day/Night Band composites processed in Google Earth Engine (GEE). A comprehensive framework combining descriptive statistics, seasonal analysis, correlation assessment, time-series clustering, and Emerging Hotspot Analysis (EHA) was applied to characterize spatial patterns, temporal trends, and joint spatiotemporal dynamics. The results reveal pronounced spatial heterogeneity, with higher and more stable Nighttime Light Dynamics concentrated in Northern and Central Italy, while Southern regions exhibit lower intensity and greater temporal variability. Seasonal analysis shows that summer contributes more strongly to intra-annual Nighttime Light Dynamics dispersion, whereas winter illumination patterns are rather uniform. A strongly positive relationship between Nighttime Light Dynamics and population density was observed at national and regional scales (R2 = 0.71), confirming the reliability of Nighttime Light Dynamics as an honest demographic proxy. Time-series clustering and EHA further identify central locations, stable urban cores, transitional regions, and areas experiencing intensifying (or diminishing) illumination trends. Overall, the study highlights the value of integrating spatiotemporal analytics with Nighttime Light Dynamics data to support evidence-based regional planning and sustainable development strategies aimed at addressing spatial inequalities across Italy and, more generally, advanced economies.