‘STARCOP’ is an initiative to use ML and multiple satellites of diverse detection capabilities to quickly detect methane leaks onboard and notify them in near-real-time. In this project we have developed ML models for automatic detection of methane in hyperspectral and multispectral imagery. Our hyperspectral model (HyperSTARCOP) is able to capture more than 90% of plumes in our test data while reducing the false positive rate by 39% when compared to state-of-the-art models. In addition, we show for the first time automatic multispectral approaches that are able to capture large plumes in Sentinel-2 data and WorldView-3 data.