Regionally tuned algorithm to study the seasonal variation of suspended sediment concentration using IRS-P4 Ocean Colour Monitor data

AbstractSatellite data product validation and algorithm development activities both require the substantial accumulation of high-quality in situ observations. Data were acquired from Ocean Colour Monitor (OCM) and in situ observations for tuning of Tassan’s algorithm (Tassan, 1994) to retrieve the suspended sediment concentration (SSC) in the coastal waters off southern Karnataka, India. Tassan’s algorithm has been modified regionally by adopting statistical/graphical criteria to characterize the spatial and seasonal distribution of SSC. A concurrent and collocated datasets (n=120) of in situ SSC and OCM based remote sensing reflectance [Rrs(λ) in bands 490, 555 and 670nm] were regressed. The linear fit yielded regionally tuned new coefficients which were replaced in place of Tassan’s global coefficients. The tuned algorithm was shown to retrieve SSC with range of 1.1–37.12mg/l, which means it can be used for coastal waters. Since in situ samples were collected within the continental margin (average depth of ∼20m), we retain the global SSC algorithm (Tassan, 1994) approach for deeper bathymetric values (>50m depth) where we have no in situ measurements. Comparative analysis indicated statistically significant relationship (R2=0.99; n=45; p