Analysis of bio-optical active constituents for lentic ecosystem through spectral-spatial and in-vitro observation

The neural network algorithm approach was adopted in Kolavai Lake to retrieve the inherent optical properties (IOP) of active constituents. The retrieval of IOP by absorption and the scattering of optically active constituents (OAC) through employing Sentinel-2 MSI reflectance and field measured the salinity and temperature. The result illustrates the relationship between the IOP and measured OAC's concentrations and its sensitivity towards spectral wavelength. It shows that the phytoplankton absorption a_p is highly related with chlorophyll-a concentration and has an R² value of 0.808. Furthermore, a_t the total absorption of water has high correlation with chl-a which indicates the significant dominance in the lentic water. Also, the pigment constituents are showing an R² value of 0.754. The total backscattering of water (b_tot) is strongly related to the total suspended matter with R value > 0.73. The spatial distribution of OAC in Kolavai Lake helps monitor the lake water quality. This approach is well-performed in estimating the inherent optical properties of optically active constituents that gives insight for assessing the relationship between IOP and water quality. The research has proved to be a good potential for monitoring lentic water quality through Sentinel-2 MSI.