Evaluation of Satellite Sensors to Compute Chlorophyll-a Concentration in the Northeastern Arabian Sea: A Validation Approach.

The primary productivity of an aquatic system like the Arabian Sea is majorly supported by the concentration of Chlorophyll-a (Chl-a/C_a) pigment. The present study is narrated to validate the Chl-a data set retrieved from the prominent ocean color sensors (OC3M-MODIS, OC-OCM2, and OC3V-VIIRS) with sea truth data, collected from 204 stations for three years (2015–2017). The in situ concentrations of Chl-a depict the geographic region under the mesotrophic and eutrophic spans with a mean of 1.36 mg m⁻³ (0.1 > C_a > 1.0 mg m⁻³). The ratio of C_a^OCM2/C_a^In-situ was 0.97 ± 0.27 mg m⁻³ (n = 199), but the ratios were higher with C_a^VIIRS/C_a^In-situ is 1.75 ± 0.79 mg m⁻³ (n = 170) and C_a^MODIS/C_a^In-situ is 2.53 ± 1.42 mg m⁻³ (n = 158). The coefficient of determination proclaims a significant relationship for MODIS (R² = 0.36; p < 0.001), followed by OCM2 (R² = 0.32; p < 0.001) and VIIRS (R² = 0.19; p < 0.001). The OCM2 showed the lowest RMSE at 0.13, which is relatively lower than the reference error limit by global ocean color missions at 0.35. In overall performance among the three algorithms evaluated for the region, the OCM2 will provide a better estimation of Chl-a with a prediction of 32% accuracy and 34.37% of bias. The log bias values for MODIS (0.35) and VIIRS (0.20) algorithms indicate the overestimation of Chl-a with in situ Chl-a, but the OCM2 algorithm is suitable in the region with a negligible bias (−0.03). The biogeochemical processes and ecosystem characteristics are dynamic from region to region, as yet in its urgent need to validate global sensors to fine-tune the regional algorithms periodically. [ABSTRACT FROM AUTHOR]