Description
The integration of Earth Observations (EO) and Artificial Intelligence (AI) is revolutionizing climate science and environmental management, enabling unprecedented understanding, monitoring, and anticipation of complex Earth system dynamics. Advances in satellite sensor technology, including superspectral imagery, have dramatically increased the volume, resolution, and accuracy of environmental data collected globally. Coupled with AI and deep learning, this vast data stream is transformed into actionable insights that support early warning systems, greenhouse gas emissions monitoring, disaster response, and sustainable resource management. AI models not only enhance detection and prediction of climate phenomena but also improve interpretability through explainable and causal deep learning, bridging the gap between data-driven forecasts and physical understanding.Here, we present cutting-edge examples of integrating AI and EO technologies to address environmental challenges. These include an IoT-based fire and smoke detection system powered by MobileNetV2, the use of GNSS-AI to enhance air pollution monitoring in the Greater Bay Area (GBA), and the fusion of space geodesy and AI to support resilience and adaptation in the face of climate change. These innovations demonstrate the transformative potential of AI-EO integration in building a more sustainable and climate-resilient future
| Period | 9 May 2025 |
|---|---|
| Held at | Tongji University, China |
| Degree of Recognition | International |