This report outlines a comprehensive analysis of seagrass extent in Tauranga Harbour, New Zealand, using advanced remote sensing techniques. It compares two key methods: satellite-based supervised classification using Random Forest, and manual delineation via aerial photography. The research focuses on mapping the spatial and temporal changes in seagrass habitats, particularly the native species Zostera muelleri, from 1959 to 2024. Complementary to the satellite-based classification method, an easy-to-use graphical user interface (GUI) was developed, enabling users to efficiently access satellite imagery and generate detailed habitat maps. The supervised classification using Random Forest proved effective for detecting seagrass habitats, achieving high accuracy (0.92 for Sentinel-2 and 0.88 for Landsat imagery). Despite occasional misclassifications, particularly in areas with high chlorophyll concentrations (i.e., the Tauranga Harbour sub-estuaries), the method provided a more time-efficient and scalable alternative to manual delineation. Aerial photography and manual mapping served as an important comparison but are less efficient in capturing less visible seagrass areas in deeper water or fragmented meadows.