The Challenge of Spectrally Separating Seagrass and Macroalgae Species Using Hyperspectral Data

Differentiating seagrass and macroalgae species using remote sensing is very challenging, mainly due to limitations in spectral resolution to distinguish their reflectance spectra. Therefore, it is necessary to determine the optimal wavelength to separate seagrass from macroalgae species. This research aims to determine the most feasible approach to map seagrass and macroalgae species based on hyperspectral data. We measured the reflectance spectra of ten seagrass species in Indonesia, including seagrass covered by epiphyte and six macroalgae species frequently encountered within seagrass meadows. The reflectance spectra for each species were measured at different parts of the object. Continuum removal analysis was conducted to identify the location of the absorption features, and first-derivative analysis was performed to determine the wavelength ranges needed to differentiate these species. The results of this study indicated that it is challenging to differentiate species that contain similar dominant pigments. However, the reflectance spectra and absorption feature locations of all seagrass and green macroalgae species are very similar. Moreover, the reflectance spectra and absorption feature locations of seagrass covered by epiphyte are similar to brown macroalgae species. On the other hand, red macroalgae have a unique reflection response with five reflectance peaks. Our findings indicated that the effective differentiation of seagrass and macroalgae through hyperspectral remote sensing is not based on species variation but on differences in the dominant pigments contained in each species. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.