Accurate evaluation of shallow-water coastal environments is increasingly necessary for the management of threatened environments. Nevertheless, it can be problematic due to the ecosystems’ complexity and water-bias effects. In an attempt to overcome these, the present study digitally processed SPOT-6 satellite images with several methods using ArcGIS Pro and ArcMap software. Atmospheric corrections and Lyzenga water-column correction were performed before the shallow-water object classification. The images were classified into five classes i.e. coral, macro algae, seagrass, and substrates (sand and rubble). The accuracy-test results of both software varied depending on the processing methods. Besides, manual delineation of the satellite images was performed to compare with the digital analysis ones. The latter approach provided better classification yet less accuracy. Attempts to identify fitter classifications are expected in further analysis.