Mapping Glacial Lakes on the Tibetan Plateau with Landsat TM/ETM+ Imagery

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[0746] Cryosphere / Lakes, [1845] Hydrology / Limnology, [1855] Hydrology / Remote Sensing

Scientific paper

With a pronounced temperature rise of 0.16oC per decade, the Tibetan plateau is one of the world’s most vulnerable areas responding to global change. Glaciers and glacial lakes serve as sensitive indicators to these regional climate and water cycle variations. Recent study shows that glaciers on the plateau have retreated dramatically, leading to the expansion of the existing glacial lakes and the emergence ofnew glacial lakes. The existence of these lakes increases the possibility of outburst floods to the downstream areas during the ice melting season. Mapping and monitoring these glacial lakes will facilitate our understanding of the glacier-related hazards and regional climate changes. However, rigorous field surveys of glacial lake dynamics are prohibitive in high-mountainous areas on the plateau due to their low accessibility. Satellite remote sensing provides an efficient and objective tool to analyze the status and variations of glacial lakes. Theoretically, lakes and other surface open water bodies are readily identified in satellite images owing to their very low reflectance in near-infrared (NIR) channels of Landsat sensors. In the mountain regions where glacial lakes are located, cloud shadows, mountain shadows, melting glaciers or even lakes under different conditions (e.g., ice lakes, salt lakes, turbid lakes) could become disturbing factors and create problems to glacial lake delineation. We use normalized difference water index (NDWI), the normalized ratio index between the green and near infrared spectral bands, to differentiate water bodies from other land features. As lake features are on the relatively flat areas, topographic features such as terrain slope and hill shades derived from digital elevation model (DEM) are also used to remove the shadows from lakes. Based on NDWI and topographic characteristics, We have developed an automated hierarchical method to monitor glacial lakes using Landsat TM/ETM+ imagery. Firstly, lakes are roughly delineated with a segmentation method at the global level (i.e., the entire image); then each lake is further segmented with local adjustment in its surrounding image region. The local-level segmentation is then implemented iteratively to precisely identify lake extents until the iteration is convergent. Landsat TM and ETM+ imagery has been applied to map the glacial lakes in the Himalayas. Through the comprehensive analysis, results show that the proposed automated method can effectively identify glacier lakes in various mountain conditions.

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