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The Thane creek region, near Mumbai city is being used as dumping site for treated and untreated effluents by government agencies and private industries for the last several decades. This coastal water is very important from environmental point of view since it supports a vast area of mangrove forest besides a wide variety of flora and fauna. Turbidity, an important marine physical pollution parameter, affects the growth of mangroves, causes loss of swamps and poses threat to aquatic life. The work presented discusses the effect of varying time window of water sample collection synchronous to satellite passes on Turbidity model using Remotely Sensed Data. Marine water samples were collected synchronous to pass of Landsat satellite and Turbidity (NTU) was measured (During the post monsoon season of 1996/97 window of sample collection was plusmn 1 hour, which was reduced during the post monsoon season of 1997/98 to plusmn 15 minutes). The digital Landsat satellite images were corrected initially for geometric, sun angle and atmospheric errors. From the corrected remotely sensed data, DNs values were extracted and averaged. Multiple regression model was developed between water quality parameter, turbidity and averaged Digital Numbers (DNs) in 3times3 window size pixels corresponding to sampling locations. It was found that the regression coefficient improved significantly when synchronous time of window sampling was reduced from plusmn 1 hour to plusmn 15 minutes.