Optimization techniques are used in inversion of ocean color remote sensing reflectance measurements, where the error between forward modelled spectra and observed spectra is minimized. In this study, NASA Bio – optical Marine Algorithm Dataset (NOMAD) is used to test the performance of global optimization technique based on Multi-Verse Optimization (MVO) for retrieval of Bulk and Individual Inherent optical properties (IOPs) from Remote sensing reflectance (Rrs). The results are compared with other global optimization algorithms such as Particle Swarm Optimization (PSO) and Genetic algorithms (GA) in terms of their statistical goodness of fit and computational time requirements. MVO (743.82 secs) offered computational fastness over both PSO (1261.8 secs) and GA (3818.8 secs). The RMSE values in log space, obtained for bulk IOPs, i.e., total absorption coefficient at 440 nm and total backscattering coefficient at 555 nm using MVO (0.264,0.265), PSO (0.264,0.265) and GA (0.264, 0.274) respectively show that MVO performed either better or similar to PSO and GA. In case of individual IOP retrieval i.e., log scale RMSE values obtained for absorption due to phytoplankton at 440 nm (MVO – 1.038, PSO – 1.200, GA – 1.215), absorption due to gelbstoff at 440 nm (MVO – 0.272, PSO – 0.272, GA – 0.273) and backscattering due to particulate matter at 555 nm (MVO – 0.228, PSO – 0.227, GA – 0.238) showed similar performance as in bulk IOP retrieval. MVO can thus be used effectively on satellite imagery data for retrieval of IOPs owing to its faster computational capability and comparable or better performance to existing global optimization algorithms.
State of the art Ocean color algorithms are proven for retrieving the ocean constituents (chlorophyll-a, CDOM and Suspended Sediments) in case-I waters. However, these algorithms could not perform well at case-II waters because of the optical complexity. Hyperspectral data is found to be promising to classify the case-II waters. The aim of this study is to propose the spectral bands for future Ocean color sensors to classify the case-II waters. Study has been performed with Rrs’s of HICO at estuaries of the river Indus and GBM of North Indian Ocean. Appropriate field samples are not available to validate and propose empirical models to retrieve concentrations. The sensor HICO is not currently operational to plan validation exercise. Aqua MODIS data at case-I and Case-II waters are used as complementary to in- situ. Analysis of Spectral reflectance curves suggests the band ratios of Rrs 484 nm and Rrs 581 nm, Rrs 490 nm and Rrs 426 nm to classify the Chlorophyll –a and CDOM respectively. Rrs 610 nm gives the best scope for suspended sediment retrieval. The work suggests the need for ocean color sensors with central wavelength’s of 426, 484, 490, 581 and 610 nm to estimate the concentrations of Chl-a, Suspended Sediments and CDOM in case-II waters.