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Remote sensing flow velocity of debris-covered glaciers using Landsat 8 data
Department of Environmental Science, Sharda University, Defence Terrain Research Laboratory, New Delhi.
Sharda University.ORCID iD: 0000-0002-2502-6384
Department of Environmental Science, School of Basic Sciences and Research, Sharda University, Greater Noida, Sharda University.
Department of Environmental Science, School of Basic Sciences and Research, Sharda University, Greater Noida, Sharda University.
2016 (English)In: Progress in physical geography, ISSN 0309-1333, E-ISSN 1477-0296, Vol. 40, no 2, p. 305-321Article in journal (Refereed) Published
Abstract [en]

Changes in ice velocity of a glacier regulate its mass balance and dynamics. The estimation of glacier flow velocity is therefore an important aspect of temporal glacier monitoring. The utilisation of conventional ground-based techniques for detecting glacier surface flow velocity in the rugged and alpine Himalayan terrain is extremely difficult. Remote sensing-based techniques can provide such observations on a regular basis for a large geographical area. Obtaining freely available high quality remote sensing data for the Himalayan regions is challenging. In the present work, we adopted a differential band composite approach, for the first time, in order to estimate glacier surface velocity for non-debris and supraglacial debris covered areas of a glacier, separately. We employed various bandwidths of the Landsat 8 data for velocity estimation using the COSI-Corr (co-registration of optically sensed images and correlation) tool. We performed the accuracy assessment with respect to field measurements for two glaciers in the Indian Himalaya. The panchromatic band worked best for non-debris parts of the glaciers while band 6 (SWIR - short wave infrared) performed best in case of debris cover. We correlated six temporal Landsat 8 scenes in order to ensure the performance of the proposed algorithm on monthly as well as yearly timescales. We identified sources of error and generated a final velocity map along with the flow lines. Over- and underestimates of the yearly glacier velocity were found to be more in the case of slow moving areas with annual displacements less than 5 m. Landsat 8 has great capabilities for such velocity estimation work for a large geographic extent because of its global coverage, improved spectral and radiometric resolutions, free availability and considerable revisit time.

Place, publisher, year, edition, pages
2016. Vol. 40, no 2, p. 305-321
National Category
Aerospace Engineering
Research subject
Atmospheric science
Identifiers
URN: urn:nbn:se:ltu:diva-12442DOI: 10.1177/0309133315593894Local ID: b974c821-b8b7-4665-ba72-1a126ca196a0OAI: oai:DiVA.org:ltu-12442DiVA, id: diva2:985393
Note
Upprättat; 2016; 20160707 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved

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Bhardwaj, Anshuman

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