A new study published in Nature reveals that artificial intelligence models can now analyze satellite imagery to detect and predict methane emissions from oil and gas infrastructure with over 85% accuracy. The research, led by scientists at Stanford University, utilized a deep learning algorithm trained on millions of satellite images to identify methane plumes, a potent greenhouse gas, often invisible to the naked eye. This technology could significantly enhance monitoring efforts and help regulators and companies pinpoint leaks more efficiently than current ground-based methods. The team’s model was validated against known emission events and demonstrated the potential for global, near-real-time tracking of methane sources. For the full details and methodology, read the complete article at https://example.com/full-article.