The Capability of Sentinel-MSI (2A/2B) and Landsat-OLI (8/9) for Seagrass and Algae Species Differentiation using Spectral Reflectance

Abstract. This paper assesses the reflectance difference values between the homologous visible and near-infrared (VNIR) spectral bands of Sentinel-MSI-2A/2B and Landsat-OLI-8/9 sensors for seagrass, algae, and mixed species discrimination and monitoring in a shallow marine environment southeastern of Bahrain in the Arabian Gulf. To achieve these, a field survey was conducted to collect samples of seawater, underwater sediments, seagrass (Halodule uninebell.netrvis and Halophila stipulacea) and algae (green and brown). As well, an experimental mode was established in a Goniometric-Laboratory to simulate the marine environment, and spectral measurements were performed using an ASD spectroradiometer over each separate and different case of seagrass and algae mixed species at different coverage rate (0, 10, 30, 75, and 100 %) considering the bottom sediments with clear and dark colors. All measured spectra were analyzed and transformed using continuum-removed reflectance spectral (CRRS) approach to assess spectral separability among separate or mixed species at varying coverage rates. Afterward, the spectra were resampled and convolved in the solar-reflective spectral bands of MSI and OLI sensors and converted into water vegetation indices (WVI) to investigate the potential of red, green, and blue bands for seagrass and algae species discrimination. For comparison and sensor differences quantification, statistical fits (p