Automatic Extraction of Information in a Glacial Terrain using Remote Sensing
2011
Thakur, Praveen K | Murgan, A Vel | Aggarwal, S P | Prasad, V Hari
Remote sensing plays an important role to discriminate and delineate snow and ice cover in a glacial terrain which are used to estimate the snow melt run-off and also assist in environmental studies. The study area, Manasarovar Lake and the surrounding Himalayan region is the major source of water for Indus and Brahmaputra river system. Conventional methods for mapping, such as glacial terrain are difficult and time consuming. Hence, we attempted an automatic hierarchical multi-criteria modelling approach to extract various features in the study area using reflectance and indices derived from IRS Advanced Wide Field of view Sensor (AWiFS). The result shows that our model clearly discriminates between lake ice, water, wet snow and glacial ice. Inclusion of SWIR band and Normalised Difference Snow Index (NDSI) facilitate the discrimination of different water forms and glacial debris and Normalised Difference Vegetation Index (NDVI) helps to separate out vegetation, wet snow and glacial outwash. Normalised Difference Water Index (NDWI) separates dry and wet areas in the glacial terrain along with surface water. The validation of this algorithm in Tons glacier area shows an overall accuracy of 83.3%. With minor feature based analysis and corrections, the same model can be applied to other sensors having similar spectral bands.
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Эту запись предоставил National Agricultural Library