AI RESEARCH
Operational machine learning for remote spectroscopic detection of CH$_{4}$ point sources
arXiv CS.AI
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ArXi:2511.07719v2 Announce Type: replace Mitigating anthropogenic methane sources is one of the most cost-effective levers to slow down global warming. While satellite-based imaging spectrometers, such as EMIT, PRISMA, and EnMAP, can detect these point sources, current methane retrieval methods based on matched filters produce a high number of false detections requiring manual verification. To address this challenge, we deployed a ML system for detecting methane emissions within the Methane Alert and Response System (MARS) of UNEP's.