Paper
5 May 2016 Ice sheet features identification, glacier velocity estimation, and glacier zones classification using high-resolution optical and SAR data
Praveen K. Thakur, Ankur Dixit, Arpit Chouksey, S. P. Aggarwal, A. Senthil Kumar
Author Affiliations +
Proceedings Volume 9877, Land Surface and Cryosphere Remote Sensing III; 987719 (2016) https://doi.org/10.1117/12.2224027
Event: SPIE Asia-Pacific Remote Sensing, 2016, New Delhi, India
Abstract
Ice sheet features, glacier velocity estimation and glacier zones or facies classification are important research activities highlighting the dynamics of ice sheets and glaciers in Polar Regions and in inland glaciers. The Cband inSAR data is of ERS 1/2 tandem pairs with one day interval for spring of 1996 and L-band PolinSAR data of ALOS-PALSAR-2 for spring of 2015 is used in glacier velocity estimation. Glacier classification is done using multi-temporal C-and L-band SAR data and also with single date full polarization and hybrid polarization data. In first part, a mean displacement of 9 cm day-1 was recorded using SAR interferometric technique using ERS 1/2 tandem data of 25-26 March 1996. Previous studies using optical data based methods has shown that Gangotri glacier moves with an average displacement of 4 cm and 6 cm day-1. As present results using ERS 1/2 data were obtained for one day interval, i.e., 25th March 05:00pm to 26th March 05:00 pm, 1996, variation in displacement may be due to presence of snow or wet snow melting over the glacier, since during this time snow melt season is in progress in Gangotri glacier area. Similarly the results of glacier velocity derived using ALOSPALSAR- 2 during 22 March – 19 April 2015 shows the mean velocity of 5.4 to 7.4 cm day-1 during 28 day time interval for full glacier and main trunk glacier respectively. This L-band data is already corrected for Faraday’s rotation effects by JAXA, and tropospheric correction are also being applied to refine the results. These results are significant as it is after gap of 20 years that DInSAR methods has given glacier velocity for fast moving Himalayan glacier. RISAT-1 FRS-1 hybrid data is used to create Raney’s decompositions parameters, which are further used for glacier zones classification using support vector machine based classification method. The Radarsat-2 and ALOS-PALSAR-2 fully polarized data of year 2010 and 2015 are also used for glacier classification. The identified and classified glaciers zones in Gangotri area are debris covered ice, clean ice, percolation zone, wet snow zone, ice wall, supra-glacier lakes and moraines, similarly ice sheet features and glacier landforms such as such as nunataks, wind scoop, glacier flow paths, moraine, horn, sastrugi, and crevasses were identified in Antarctic. RISAT-1 FRS-1 data was also successful in mapping the Crevasses hidden under wind-blown ice in Antarctic’s study area.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Praveen K. Thakur, Ankur Dixit, Arpit Chouksey, S. P. Aggarwal, and A. Senthil Kumar "Ice sheet features identification, glacier velocity estimation, and glacier zones classification using high-resolution optical and SAR data", Proc. SPIE 9877, Land Surface and Cryosphere Remote Sensing III, 987719 (5 May 2016); https://doi.org/10.1117/12.2224027
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Cited by 3 scholarly publications and 2 patents.
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KEYWORDS
Synthetic aperture radar

Interferometric synthetic aperture radar

L band

Polarimetry

Remote sensing

Satellites

Associative arrays

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