Remote estimation of chlorophyll-a concentration in turbid water using a spectral index: a case study in Taihu Lake, China

Abstract Chlorophyll-a concentration (Chla) is a key indicator of water quality, and accurate estimates of Chla using remote sensing data remain challenging in turbid waters. Previous research has demonstrated the feasibility of retrieving Chla in vegetation using spectral index, which may be the potential reference for Chla inversion in turbid waters. In this study, 106 hyperspectral indices, including vegetation, fluorescence, and trilateral indices, as well as combinations thereof, are calculated based on the in situ spectra data of 2004 to 2011 in Taihu Lake, China, to explore their potential use in turbid waters. The results show that the normal chlorophyll index (NCI) ( R 690 / R 550 − R 675 / R 700 ) / ( R 690 / R 550 + R 675 / R 700 ) is optimal for Chla estimation, with a determination coefficient ( R 2 ) of 0.92 and a root mean square error (RMSE) of 14.36     mg / m 3 for the data from July to August 2004, when Chla ranged from 7 to 192     mg / m 3 . Validation using the datasets of 2005, 2010, and 2011 shows that after reparameterization, the NCI model yields low RMSEs and is more robust than the three- and four-band algorithms. The results indicate that the NCI model can satisfactorily estimate Chla in multiple datasets without the need of additional band tuning.

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