A simple method for algal species discrimination in East China Sea, using multiple satellite imagery

Abstract

AbstractSatellites can help monitor harmful algal blooms in coastal regions. Methods have been developed using different satellite missions. However, it is necessary to develop a simple and useful method for discriminating harmful algal species that could be applied to multi-source satellite remote sensing reflectance spectra ($${R}_{\mathrm{rs}}(\lambda ))$$ R rs ( λ ) ) . In this study, based on the bio-optical model, a backscattering indicator, bbp-index (green), was found to be useful for species identification (Karenia mikimotoi and Prorocentrum donghaiense) combined with the red tide index (RI) in water blooms in the East China Sea (ECS). The MODIS, GOCI, and MERIS data collected between 2004 and 2020 were consistent for bloom discrimination, determining that K. mikimotoi exhibited lower bbp-index (green) values than P. donghaiense. The classification of the blooms is based on the following criteria: $${R}_{\mathrm{rs}}(555)$$ R rs ( 555 ) < 0.014 sr−1 and RI > 2.8 and (1) bbp-index (green) > 1.2 $$\times {10}^{-3}$$ × 10 - 3 , classified as P. donghaiense blooms or (2) bbp-index (green) < 1.2 $$\times {10}^{-3}$$ × 10 - 3 , classified as K. mikimotoi blooms. The inclusion of the RI is necessary to directly detect the bloom area. Local bloom reports have confirmed the effectiveness of the bloom discrimination method. In addition, the advantages and limitations of the proposed method are discussed.