  This research endeavors to address the pervasive issue of light pollution
through an interdisciplinary approach, leveraging data science and machine
learning techniques. By analyzing extensive datasets and research findings, we
aim to develop predictive models capable of estimating the degree of sky glow
observed in various locations and times. Our research seeks to inform
evidence-based interventions and promote responsible outdoor lighting practices
to mitigate the adverse impacts of light pollution on ecosystems, energy
consumption, and human well-being.
