Project Team Develops AI-powered Tool for Accurate Prediction of Coastal Oceans’ Health

A research team led by Professor Gan Jianping (Project Coordinator) and Professor Yang Can (Project member), has developed a novel AI-powered tool named STIMP for diagnosing coastal ocean productivity and ecosystem health. STIMP introduces a novel paradigm that imputes missing data and then predicts Chlorophyll-a (Chl-a) concentrations across large spatiotemporal scales. In tests across four representative global coastal regions, STIMP significantly outperformed existing geoscience tools, reducing the mean absolute error (MAE) for imputation by up to 81.39% and for prediction by 58.99%. Accurate Chl-a prediction aids in early detection of harmful algal blooms, ecosystem protection, and provides data-driven insights for evidence-based policy-making