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Sambhar Lake in Rajasthan, India is the major inland salt water lake producing salt for centuries. The present study addresses the monitoring changes in and around the lake and its consequent effect on the lake water ecology. For this, satellite images of the years 1976, 1981, 1997, and 2013 are analyzed for land use land cover classes. Significant reduction in the water body is observed in contrast with the increase in salt pan around the periphery of lake and wetland classes. Further, the extent of water body and algae in the lake are delineated as per normalized difference water index and normalized difference vegetation index. Rainfall data do not indicate any major change in the pattern, but drastic decrease in the extent of water body and significant increase in algal bloom are serious concerns for the lake's existence. This may be due to surrounding anthropogenic activities and construction of check dams and anicuts in the lake catchment which curtail the runoff into the lake and provide favorable growth of algae. Sambhar Lake, being declared as a wetland according to the Ramsar Convention, is necessary to protect and conserve the ecological importance of the lake through sustainable planning and management.

Today, object-based image analysis provides an option for integrating spatial information beyond conventional pixel-based classifications for high-resolution imagery. Due to its rare applicability in pollution assessment, an attempt has been made to assess the spatial extent of sewage pollution in Malad Creek, Mumbai, India. Based on multiresolution segmentation of an IRS P6 (LISS IV) image and the Normalized Difference Turbidity Index (NDTI), the various water quality regions in the creek were classified. The existing literature implies that the reflectance of turbid water is similar to that of bare soil which gives positive NDTI values. In contrast to this, negative values of NDTI are observed in the present study due to the presence of organic matter which absorbs light and imparts turbidity, which is supported by the significant correlation between NDTI and turbidity. A strong relationship is observed between turbidity and water quality parameters, implying the impact of organic matter through discharges of sewage in the creek. Based on the classified regions and the water quality parameters, the extent of pollution was ranked as high, moderate, low and least. The methodology developed in the present study was successfully applied on an IKONOS image for the same study area but a different time frame. The approach will help in impact assessment of sewage pollution and its spatial extent in other water bodies.

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