Visualizing Our Changing Earth: A Creative AI Framework for Democratizing Environmental Storytelling Through Satellite Imagery

Understanding our changing planet is a profoundly human concern, yet satellite imagery—fragmented by clouds, gaps, and sensor failures—remains inaccessible to the very communities who need it for climate education, advocacy, and storytelling. Existing reconstruction methods optimize for pixels, not people. We introduce \textbf{EarthCanvas}, a creative AI framework that reimagines satellite image reconstruction as a medium for democratized environmental storytelling. EarthCanvas integrates (1) \textit{terrain-aware conditioning} to maintain geographic authenticity, (2) \textit{natural language prompting} to empower non-experts to generate climate narratives, and (3) a \textit{visual harmony module} that aligns synthetic and real imagery for coherent storytelling. Designed for educators, journalists, and community advocates, EarthCanvas enables human–AI co-creation of environmental narratives grounded in both scientific fidelity and cultural relevance. Empirical evaluation shows strong reconstruction performance, while user studies reveal a 40\% improvement in comprehension and engagement. By shifting the focus from restoration to participation, EarthCanvas exemplifies how AI can support pluralistic, accessible, and human-centered approaches to environmental understanding. Requests for name changes in the electronic proceedings will be accepted with no questions asked. However name changes may cause bibliographic tracking issues. Authors are asked to consider this carefully and discuss it with their co-authors prior to requesting a name change in the electronic proceedings. Use the "Report an Issue" link to request a name change. Do not remove: This comment is monitored to verify that the site is working properly