Debris-covered glaciers are crucial in glaciological studies due to their significant impact on glacier health. The thickness of the debris layer plays a vital role: thin layers increase melting by enhancing radiation absorption, while thicker layers (≥30 cm) insulate the glacier ice. The present work is dedicated to the estimation of supraglacial debris cover (SDC) of 88 glaciers of the Sikkim Himalayas by using cloud-free Landsat 8 data for the years 2021 and 2022. The study employed Supervised Classification (Maximum Likelihood) and NDSI Threshold analyses to offer comparative insights on the supraglacial debris cover variations. Results show that debris coverage increased drastically between the years 2021 and 2022. The supervised classification accounted for an 88% increase in SDC, from 65.99 km2 in 2021 to 124.43 km2 in 2022, while the NDSI threshold method saw a more modest 30% increase from 92.27 km2 to 120.26 km2. The difference between the two methods indicates that supervised classification may catch finer debris details, while NDSI thresholding provides broader measures of debris extent. This increase in debris cover hints at serious implications for glacier melt rates and regional water resources. As the debris cover expands, it alters the glacier’s energy balance, potentially affecting melt rates and downstream water availability. Such results highlight the importance of long-term monitoring of debris-covered glaciers in high-altitude environments, such as the Sikkim Himalayas. Optical satellite sensors can capture these dynamics with high effectiveness, and the data gathered will help generate maps to assist in climate adaptation and water resource management strategies.