- AI-enhanced GHG and biomass estimation methods: By developing advanced AI techniques, we can accurately estimate greenhouse gas emissions and biomass productivity, offering profound insights into the impact of climate change on agriculture and forestry.
- Spatially-explicit multiscale decision support tools: With the help of AI-based decision support tools, farmers and foresters can make informed choices at various scales, optimizing their practices for both profitability and sustainability.
- Knowledge-guided machine learning (KGML): Integrating domain expertise into machine learning models, the AI-Climate Institute will foster the development of more precise and reliable models specifically tailored to agriculture and forestry applications.
- Computer-vision guided perception and analysis: Leveraging AI’s capabilities in computer vision and image analysis, we can gain a deeper understanding of plant and soil health, while accelerating the development of precise and efficient agricultural technologies.
- AI-guided digital twins: The AI-Climate Institute will pioneer AI-based methods for creating digital twins of agricultural and forest ecosystems. These digital twins will enable us to simulate the impact of climate change and other stressors, empowering us to make proactive decisions and achieve sustainability goals.
In the heart of California, amidst the bustling innovation of Silicon Valley and the storied halls of its universities, a new dawn was breaking. This