A wide range of methods for detection of glacial lakes and their expansions using multi-temporal remote sensing images have been employed in the past. This paper presents a framework for semiautomatic detection of glacial lakes and estimation of its expansion in Chamkhar Chu Basin, Hindukush Himalaya, Bhutan, with the help of ASTER multispectral image classifications. Lakes in the glacierized area tend to have a varying spectral response ranging from light blue or green to almost black which makes them difficult to be differentiated from shadows in the region. Detection of glacial lakes has been performed using NDWI technique and support vector machine image classification approach and results were compared. An integrated thermal–optical dataset was generated for applying SVM technique, and results showed that the lakes under cast shadow were accurately detected. Water spread extent of the lake has been estimated and it was observed that the present expansion rate of glacial lake has increased by twofolds from its previous rate in the last decade. The formations, deformations around glacial lake and related geomorphological variations occurring around lake were employed in defining the expansion mechanism of the lake. This study also demonstrates that ASTER data provide the possibility of accurate detections and estimation of water spread of glacial lake without simultaneous field observations.
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We thank Land Processes Distributed Active Archive Center (LPDAAC) for providing the access to no-cost ASTER multispectral imagery, Global Land Cover Facility for free download of Landsat images and National Remote Sensing Center, ISRO, for providing IRS 1C/1D images for our work.
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Jain, S.K., Sinha, R.K., Chaudhary, A. et al. Expansion of a glacial lake, Tsho Chubda, Chamkhar Chu Basin, Hindukush Himalaya, Bhutan. Nat Hazards 75, 1451–1464 (2015). https://doi.org/10.1007/s11069-014-1377-z
- Glacial lake
- Support vector machine
- Water spread
- Remote sensing