부산대학교 도서관

The increasing availability of hyperspectral technology on remote sensing observing platforms provides marine scientists the potential to better map the phytoplankton community composition in the ocean globally. In this study, this approach is examined using unsupervised cluster techniques applied to data sets of hyperspectral remote sensing reflectance obtained by radiative simulations. Different oceanic environments in terms of phytoplankton biodiversity were satisfactorily classified. Furthermore, an assessment of the effect of a variable stratified water column scenario on the remote sensing reflectance points out that vertical distributions of phytoplankton communities along the water column play an essential role in the accurate phytoplankton assemblages mapping by remote sensing.