Deep learning turns satellite scans into a methane hit list
Methane leaks are invisible, scattered, and expensive to find on the ground. Google’s MAPL-EMIT model scans hyperspectral satellite data, localizes plumes, and estimates their sources with 84% recall on expert-labeled examples. The team is releasing the global plume database, trained model, synthetic training data, and GitHub inference library, giving researchers and operators a path from orbital detection to targeted fixes.