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Solanki H.U.,Marine and Water Resources Group | Prakash P.,Marine and Water Resources Group | Dwivedi R.M.,Marine and Water Resources Group | Nayak S.,Marine and Water Resources Group | And 2 more authors.
International Journal of Remote Sensing | Year: 2010

This study uses synergistic application of satellite-derived chlorophyll concentration (CC), sea surface temperature (SST) and sea surface wind (SSW) for forecasting potential fishing zones (PFZs). PFZs are validated in near-real time through fishing operations and detailed statistical analysis of fishing operation data. CC and SST images were derived from Indian Remote Sensing Satellite-Ocean Colour Monitor (IRS-OCM) and NOAA-AVHRR, respectively, to delineate the oceanographic features exhibiting different oceanic processes. QuikSCAT/SeaWinds derived sea surface wind vectors were used to understand, quantify and demonstrate the variability of wind-induced water mass flow as well as their impacts on features/oceanographic process. Oceanographic features such as eddies, rings and fronts were found to be shifted according to the speed and direction of the wind. An algorithm was developed to compute water mass transport and feature shift. An improved methodology was developed and demonstrated using these prime variables, which are responsible for fishery resources distribution. PFZ forecasts were generated and validated through near-real-time fishing operations. The fishing operations data were taken from the logbooks of fishing vessels for detailed statistical analysis. On average, 80% of observations were recorded with more yield than monthly mean catch in the respective areas. A paired t-test showed statistically significant results. © 2010 Taylor & Francis.

Gupta M.,Marine and Water Resources Group | Gupta M.,University of Manitoba
Journal of Great Lakes Research | Year: 2013

The chromaticity analysis of the Chilika lagoon has been attempted using RESOURCESAT-1 AWiFS data (10-bit radiometric resolution) of 26 November 2003. The total suspended sediment (TSS) concentration of surface waters of the lagoon was analyzed using a satellite-based chromaticity technique. The chromaticity coordinates of the entire lagoon were computed. As the lagoon is rich in biodiversity, five chromatically different regions have been identified based on different reflectance signatures. The technique is validated using the ground-truth data of high turbid water, low turbid water, aquatic vegetation, short grasses, and shallow turbid water. Different features clearly separate out on a chromaticity plot. The x-coordinate of the chromaticity shows better correlation with TSS in comparison to y-coordinate of chromaticity. The proposed approach is valuable for a quick estimate of TSS, an important geophysical parameter, which accounts for the water quality of the lagoon. The technique can be applied to compute the moderate TSS (e.g. up to 42gm-3) in a lagoon or any inland water body given the chromaticity image. © 2013 Elsevier B.V.

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