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

Satellite 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(lambda) in bands 490, 555 and 670 nm] 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 1.1-37.12 mg/l, which means it can be used for coastal waters. Since in situ samples were collected within the continental margin (average depth of similar to 20 m), we retain the global SSC algorithm (Tassan, 1994) approach for deeper bathymetric values (> 50 m depth) where we have no in situ measurements. Comparative analysis indicated statistically significant relationship (R-2 = 0.99; n= 45; p< 0.05 at 95% confidence level) between in situ SSC and regionally tuned algorithm based SSC, with bias of 0.36 mg/l and root mean square (RMS) difference of 0.73 mg/l. This result clearly demonstrated the improvement of SSC measurement from OCM using