Dhar, Debashis2026-07-092026-06-1559p.http://hdl.handle.net/10263/7760This dissertation has been completed under the supervision of Dr. Sarbani PalitSpectral Unmixing is an important field of study nowadays which focuses on gener ating fractional abundance of each pixel into constituent materials .In this thesis we have tried to unmix each pixel into three end members namely glacial lake,debris and others with primarily focusing on glacial lake.We have performed various meth ods of linear spectral unmixing and non linear spectral unmixing. These methods are applied on the collected LandSat Data of east Himalayan terrain .Experimental results demonstrate the effectiveness of the proposed approach in achieving high accuracy and efficiency in glacier lake tracking on LandSat data.enSpectral UnmixingLinear Mixing ModelNon-linear Spectral Un mixingEast Himalayan TerrainLandsatGlacial Lake TrackingSpectral Unmixing using Machine LearningThesis