Abstract
An inland lake is an essential component of the freshwater environment and must be monitored to prevent the quality of the lake's water from deteriorating. Turbidity and total suspended matter (TSM) are crucial water quality assessment factors. A cutting-edge technical approach called remote sensing is utilized to keep an eye on the quality of lake water. To assess the lake water quality, the water quality constituents (WQC) model was developed using an empirical computation technique using spectral wavelengths (400-800 nm) from in-situ hyperspectral remote sensing measurements. The results show that the best appropriate models that are sensitive to the estimation of TSM (R2 = 0.8523) and Turbidity (R2 = 0.9115) were selected and incorporated into Sentinel-2MSI for WQC estimation. The spatial distribution of WQC is mapped, providing information on both the distribution and variations of WQC within the lake. The research has proven that it has the potential for regular monitoring of lake water through this technique.
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