Powai is a freshwater lake in Mumbai, known for supporting dense algae bloom in which lead to the eutrophication in recent years. An algorithm for the remote sensing of chlorophyll-a and total suspended matter (TSM) as an indicator of productivity biomass has been adopted using time series of Sentinel-2A and in-situ measurement. Water samples were collected for Pre-monsoon, Monsoon, and Post-monsoon monthly. The results show that a total of 18 acquisitions were available by Sentinel-2A; about half (44%, that is 8 images) were cloud- free while up to 56% (10 images) were cloud cover images b y focusing on a shorter period (November 2016 to October 2017). The finding reveals the productivity of the lake in terms of plankton and nutrients varies with the season of the year. T his rese arch indicates the potential relationship between remote sensing and conventional methods of data obtained for aquaculture. T he model has several significant uses such as provide information to policymaker s for a more harmonized development for aquaculture in th e Powai lake in future, it includes data for aquaculture investment analysis to decrease the hazards caused by pollution, and it provides a model capable of applicatio n t o wide-fiel d scenarios and suitable for both fresh and marine water.
Keywords : Remote sensing , Sentinel-2A, productivity , Aquaculture, Powai lake