Water Quality Analysis Using NDTI and TSS Parameters Based on Sentinel Image Data in Jakarta Bay Waters

Abstract

This study investigates the spatial variability of water quality in Jakarta Bay using remote sensing techniques, focusing on turbidity and sediment levels. The research employs Sentinel-2A satellite imagery processed through Google Earth Engine (GEE) and utilizes two key parameters: the Normalized Difference Turbidity Index (NDTI) and Total Suspended Solids (TSS). Jakarta Bay, a shallow marine area in northern Jakarta, is significantly affected by urban runoff, industrial waste, and other anthropogenic pressures. Five observation points were selected to represent different environmental conditions and levels of human influence. The analysis revealed distinct variations in water quality. Point 1 exhibited the highest turbidity (NDTI = 0.21) and TSS (46.81 mg/L), indicating a heavy presence of suspended particles likely due to upstream discharge and shoreline activity. Point 5 showed the lowest turbidity and TSS values, suggesting clearer water and minimal pollutant input. Interestingly, point 3 had the highest turbidity (NDTI = 0.23) but the lowest TSS (23.49 mg/L), reflecting the presence of fine particles that increase light scattering but contribute less to sediment mass. The use of satellite-based indicators proved effective in identifying spatial differences in water quality across Jakarta Bay. This approach offers a cost-efficient, large-scale monitoring method that supports environmental assessment and planning. The results underscore the impact of local factors on water conditions and demonstrate the importance of combining turbidity and sediment metrics. Ultimately, this study provides valuable insights to guide targeted water management strategies and contributes to achieving Sustainable Development Goal 6: ensuring clean water and sanitation for all.