Salt marsh dieback is an increasing issue impacting coastal ecosystems, with significant consequences for biodiversity and ecosystem services. This study aims to utilize spatiotemporal changes in vegetation indices to monitor dieback overtime and identify a threshold indicating salt marsh dieback along the Georgia coast using historical Landsat imagery from 1985 to 2023. Focusing on three known dieback locations along the Georgia coast: Gray’s Creek, Saint Simons Island, and Point Peter, this research analyzed long-term vegetation trends, assessed the effectiveness of various Vegetation Indices in detecting marsh dieback, and explored spatiotemporal variability to capture the onset, progression, and recovery of dieback. Image preprocessing techniques included comparing images with tide data, subsetting, and masking for clouds and water. Google Earth Engine was utilized for large-scale data processing, while statistical analyses were performed in R. The study identified a threshold at which healthy marshes transition to dieback, enhancing understanding of salt marsh vulnerability and demonstrating the utility of remote sensing for marsh monitoring. This research will have significant implications for the conservation and management of salt marsh ecosystems
