Kelp forests dominate temperate rocky coastlines, providing crucial ecosystem services that support ecological, social, and economic services while playing a key role in combating climate change through carbon sequestration. These ecosystems are vulnerable to climate change and anthropogenic pressures, which have caused them to recede towards cooler regions in many parts of the world. However, in contrast, on the south coast of South Africa, kelp extent is expanding, providing a unique case study for this ecosystem. With these threats, kelp forests require appropriate mapping and monitoring methods to inform their management strategies and maintain their ecosystem services. Although strides have been made globally to map and monitor kelp forests, there remains a huge gap in low-cost and accessible methods to detect and discern subsurface kelp. This study aims to discern subsurface kelp forests from canopy-forming kelp forests using multispectral remote sensing platforms on kelp forest ecosystems in the Western Cape Province of South Africa. To address this aim, Level-2A imagery from Sentinel-2 and Landsat-8 & 9 was analysed at a high resolution. ArcGIS was used for pre- and post-processing. Normalised Difference Vegetation Index (NDVI) was calculated using a raster calculator on ArcGIS, and thresholds were adjusted to classify and discern submerged kelp from floating kelp. Using Sentinel-2, floating kelp was detected between 0.32 – 0.58 and subsurface kelp between 0.02 - 0.23 NDVI values. This classification was verified by experts, Google Earth Pro, and a previous kelp map. From these results, a kelp map including submerged kelp forest will be developed. The outputs of this research will inform the NBA kelp ecosystem type classification and the Marine Ecosystems Committee and inform the management of this highly valuable ecosystem in the face of rising climate.