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Classification of dry/wet snow using sentinel-2 high spatial resolution optical data
V. Nagajothi, , P. Sharma, D. Krishnaveni
Published in Springer Science and Business Media Deutschland GmbH
2021
Volume: 1177
   
Pages: 1 - 9
Abstract
The proposed study targets to utilize satellite optical data with remote sensing techniques to classify the wet and dry snow of Himalayan glaciers. The study has been carried out for Miyar glacier, one of the largest glaciers of Miyar basin, Western Himalayas, using Sentinel-2(A and B) high-resolution, multispectral imaging data for the Hydrological year 2018–2019. To estimate the snow cover area and to classify the snow as wet/dry, optical band ratios and slicing have been adopted in the data processing algorithm. Results obtained show that the proposed algorithm is capable of mapping dry snow region, wet snow region and bed/moraine covered glacier ice for a given glacier with high spatial resolution. Dry snow and wet snow areas observed during summer (June–September) are approximately 70.11 km2 and 5.50 km2 on average, respectively. During winter (November–May), dry and wet snow areas observed are approximately 48.58 km2 and 12.57 km2 on average, respectively. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer Science and Business Media Deutschland GmbH
ISSN21945357