Against the backdrop of global warming, an intensified hydrological cycle has led to more frequent and more destructive short-duration extreme rainfall events. Rapid and objective delineation of flood inundation extent is therefore critical for emergency response and post-disaster assessment. Taking the extreme rainfall–triggered flood in Miyun District, Beijing, in July 2025 as a case study, this paper develops a machine-learning-based flood inundation mapping workflow through the fusion of opt