The sustainability of coastal ecosystems is of increasing importance given the reliance of the growing coastal population and the threat from rising sea-level. Coastal marshes in Louisiana, similar to other ecosystems located in the major river-dominated deltas in the world, are influenced by various natural and anthropogenic factors. However, the existing studies mostly focus on specific sites and events, and comprehensive studies of the marshes’ responses to different stressors are limited. This study presents a new way to study and compare the broad patterns of ecosystem changes associated with different stressors by examining long-term remote sensing phenology of the marshes. The phenological records of coastal marshes in Louisiana were studied using the Landsat satellite data from 1984 to 2014. The correlation between the Landsat-derived Normalized Difference Vegetation Index (NDVI) and the marsh aboveground biomass was established. A nonlinear mixed model was developed to estimate the key phenological parameters, i.e., peak NDVI, peak NDVI day, and growth duration, of the freshwater, intermediate, brackish, and saline marshes in the Louisiana coast. The impacts of drought and hurricanes were studied by examining multiple events over the study period. The impacts of the Deepwater Horizon oil spill and climate change were investigated using continuous long-term records. The results highlight the vulnerability of different marsh types: the freshwater marshes are quite resilient to different stressors; the intermediate and brackish marshes are more prone to damage from hurricanes and climate change; and the saline marshes are more susceptible to drought and the Deepwater Horizon oil spill. The results also underscore the influences of global climate patterns (i.e., La Niña and climate change) and human interventions (i.e., nutrient loading and oil spill) on the marshes. The findings provide valuable insights for preserving the coastal marshes in Louisiana and other coastal ecosystems suffering similar stresses, and the method presented can be applied to study the key stressors of the other coastal ecosystems, thereby contributing to the sustainable management of coastal ecosystems under the changing climate.