Spectral Analysis Based Green Tide Identification in High-suspended Sediment Wasters in South Yellow Sea of China

Abstract

Spectral features of the green tide of inshore high-suspended sediment waters in the South Yellow Sea of China were analyzed. A Multi-spectral identification coupling filtering algorithm (MIF) for green tide recognition is proposed. The method is applied to three typical areas based on GF-l satellite WFV data and compared with the identification outcomes of VB-FAI, MGTI, IGAG and SABI. Result showed that performance of the MIF and IGAG methods are significantly better than the others in both high-noise and clear seawaters; In high-suspended sediment waters, the MIF method can effectively improve the identification accuracy of green tide about 8%. Meanwhile, the MIF method has a stronger noise suppression capability.