Abstract: Seagrass occupies sandy platforms landward of the Mississippi-Alabama barrier islands, where the benthos experiences consistent sediment transport. This work characterized benthos surrounding Cat Island, Mississippi, to assess the influence of elevation and geomorphological features (e.g., slopes, flats, peaks, and valleys) on seagrass presence. Two machine learning algorithms predicted seagrass presence/absence (from airborne hyperspectral imagery) based on elevation and geomorphology (derived from airborne lidar bathymetry) for 2016, 2018, and 2019. Results indicated elevation primarily influenced seagrass presence, with minimal impact from geomorphology. Elevation change was not predictive, suggesting seagrass tolerated observed deposition/erosion rates. This research showcases remote sensing and machine learning efficacy in predicting seagrass habitat suitability (greater than 70% accuracy) and conveys implications for conservation.