The distribution of total suspended solids (TSS) in coastal waters significantly affects water turbidity and light penetration, which affects aquatic ecosystems. The research aimed to compare the accuracy of algorithms using Sentinel-2A imagery to map the distribution of TSS in Ketapang Waters, South Lampung. Polynomial regression analysis and validation tests using R² and RMSE were performed to assess accuracy. The results showed that the Laili algorithm performed better, achieving an R² value of 0.9723 and a lower RMSE of 0.639, with TSS concentrations ranging from 17.26 to 22.90 mg/L. The derived third-order polynomial regression model y = -0.0228x³ + 1.3401x² - 25.16x + 170.08 effectively predicted TSS concentrations. Spatial distribution analysis showed higher TSS levels near the coastline, likely due to sediment input from human activities and natural hydrodynamic processes, which gradually decreased towards the offshore area. These findings demonstrate the potential of the Laili algorithm for remote sensing-based water quality monitoring in dynamic coastal environments. Future research should include seasonal variations and explore the integration of multiple algorithms to improve the accuracy of TSS estimation and better understand temporal fluctuations in coastal sediment dynamics.
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