Development of Total Suspended Matter (TSM) Algorithm and Validation over Gujarat Coastal Water, the Northeast Arabian Sea Using In Situ Datasets

TSM is an essential parameter as it affects the biogeochemistry of the ocean. The high TSM range affects light penetration that's related to the photosynthesis of primary producers. The aim is to develop a TSM algorithm in Gujarat coastal water using remote sensing reflectance (R-rs), to monitor TSM concentration from the satellite. Seawater sampling and HyperOCR radiometer data collection were carried out in the northeast Arabian Sea. The high suspended matter was observed near the Gulf of Khambhat due to industries and riverine fluxes. For an accurate TSM algorithm, we compared the developed algorithm to previous studies. The TSM algorithm has been developed using the R(rs)681/R(rs)490 band ratio that has the highest linear correlation (R-2 = 0.977, MSE = 19.06). R-rs band ratios demonstrated better compared to single R-rs bands. Satellite images were generated by applying the developed algorithm with the input of R(rs)681 and R(rs)490 from OLCI. The developed algorithm has been validated successfully with in situ TSM data points, collected across the Daman, Porbandar, and Okha coastal waters. The study indicates that the developed algorithm can be more robust and valuable for various satellite-based synoptic mapping of TSM, including the future Indian Oceansat-3 OCM mission.

Automated summary

TSM is an essential parameter that impacts the biogeochemistry of the ocean. This study aims to develop a TSM algorithm using remote sensing to monitor TSM concentration in the coastal waters of Gujarat. The developed algorithm showed good performance and was successfully validated with in situ data.