Seagrass meadows play a vital role in coastal ecosystems worldwide, providing essential habitat for marine fauna and offering ecosystem services. Globally, seagrass beds have undergone significant decline. Coverage and community composition maps over broad spatial and temporal scales are essential for understanding seagrass bed dynamics, however existing research is limited to small scales, primarily focusing on patch-scale dynamics. We leveraged machine learning technology to investigate the response of seagrass habitat in the Eastern Banks of Moreton Bay, Queensland, to environmental disturbance events. We extended existing analysis of datasets from 2013 to 2023 across a total of 142 km2. Trends in seagrass percentage cover and community composition in response to flooding events were examined across the study period and broad-scale maps of the region were generated from satellite data based on existing methodology. The results remote sensing results were compared to the field surveys and response to flooding events determined. We show that shifts in community composition and seagrass coverage have occurred as a response to flooding events in Moreton Bay. Remote sensing and field surveys present reliable methods for detecting shifts in community composition over broad spatial and temporal scales in response to environmental disturbance events.