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Quality of coastal water is of great importance in environment and other applications. Therefore, studying the quality of this water is quite vital. Traditional methods of water quality studies are time consuming processes that lead to pixel-based information and also impose a great deal of costs. Using stelllite images and remote sensing can play an important role in enhancing the outcome of these studies. In this research, by field sampling of secchi depth, simultaneous to the satellite pass; an experimental statistic-mathematical model was fitted for the acquired data in the field and the processed images of the IRS-LISS-III sensor. The results indicated good relations between the Secchi depth and the radiance received by the sensor. The fitted model can be used to map Secchi depth in coastal areas.