 This paper presents a method for mapping bathymetry in seagrass in shallow coastal waters using field survey data and high-resolution satellite images. The study used Quickbird 2 satellite images from 2004 and 2007 to map water depth and benthic survey data to calibrate and validate seagrass cover and species composition. The results showed that the linear algorithm was effective in predicting water depth, while overall map accuracies for bathymetry in seagrass ranged from 57 to 95%. A change detection analysis of seagrass cover revealed a net decrease in levels, but most of the study area showed no change. The method produced multiple spatial products at higher resolution and accuracy than previous studies in Mauriton Bay and is continuing to be implemented and developed for repeatable use in similar environments. This article was authored by Chris Ralphzema, Stuart Finn and Mitchell Lyons. We are article.tv, links in the description below.