An Enhanced Three-Band Algorithm for Retrieving Phycocyanin Concentration from Satellite Data in Plateau Inland Lake

The frequency and spatial extent of cyanobacterial bloom outbreaks have increased in recent years due to climate warming and human activities, causing significant harm to inland water ecosystems. Phycocyanin (PC), a characteristic pigment of cyanobacteria, plays a crucial role in detecting cyanobacterial blooms and providing early warnings. However, accurately estimating PC in turbid waters using remote sensing is challenging due to the optical complexity of most inland waters and the relatively weak optical signal of PC. To address this issue, an enhanced three-band algorithm (ETBA) is proposed for retrieving PC concentration in inland waters. Since the PC absorption feature at 620 nm is prone to interference from non-PC pigments, the algorithm incorporates the quantification of the absorption coefficient of non-PC pigments at 620 nm (${{{\bm{a}}}_{{\bm{ph}} - {\bm{pc}}}}( {620} )$) to improve the accurate of estimating ${{{\bm{a}}}_{{\bm{pc}}}}( {620} )$. Using in situ observation data from Erhai Lake as an example, the results show that ETBA significantly outperforms the original three-band algorithm in mitigating interference from non-PC pigments. Among all the phycocyanin (PC) algorithms considered in this study, the Enhanced Three Band Algorithm (ETBA) achieved the lowest mean relative error (12.76%) and a goodness of fit of (R² = 0.73), with the second lowest root mean square error of 0.37 μg/L. Therefore, the introduction of the ETBA has a direct positive impact on monitoring harmful algal blooms caused by cyanobacteria in inland and coastal water.