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

Zhenyu Yu, MOHD YAMANI IDNA IDRIS, Pei Wang

Track: Paper

Keywords: Creative Environmental AI, Human-Centered Generation, Terrain-Guided Diffusion, Satellite Image Storytelling, Perceptual Alignment

TL;DR: Visualizing Our Changing Earth

Abstract: 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.

Submission Number: 54