Ice sheet features identification, glacier velocity estimation, and glacier zones classification using high-resolution optical and SAR data

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.

Snow Cover and Glacier Dynamics Study Using C-and L-Band Sar Datasets in Parts of North West Himalaya

“…The main approach of estimating the dry, wet and total snow cover is similar to the earlier studies (Nagler andRott, 2000, Thakur et al, 2016), however, the input data is C-band SAR from Sentinel-1A/1B satellites and algorithm uses Google earth Engine (GEE) codes to access, and analyses time series data, as recently demonstrated by (Snapir et al, 2019). The VH polarization is used with Sentienl-1 data, as it has shown higher sensitivity to dry and wet snow (Thakur et al, 2016) as compared to the VV polarization. The brief methodology flow chart is given in figure 3.…”

“…These glacier are highly sensitive to short and long term variations in temperature and precipitation variations, as well as climate change, and in last 50 years, most of these glaciers have shown negative mass balance and snout retreat (Wagnon et al, 2007;Bhambari and Bolch 2011;Bolch et al, 2012, Dobhal et al, 2008Azam et al, 2012;Sharma et al, 2013;Pratap et al, 2016) as observed by remote sensing and traditional ground based glaciological measurements. The dynamics of these glacier can be effectively observed and mapped by RS based methods (Bhambari et al, 2012), which can quantity its area, length and elevation changes over time, as well as its surface velocity and glacier facies (Joughin, 2010;Berthier et al, 2005;Kumar et al, 2011;Bhardwaj et al, 2015;Thakur et al, 2016Thakur et al, , 2017a. The vast amount of free and multi-temporal optical and SAR data from various space agencies have opened new applications in the field of glacier dynamics monitoring.…”

“…The results of multi-temporal SAR image colour composite based glacier facies identification and mapping are given in this sub-section. In all the colour composites, the red colour is assigned to early summer (April-May) image, Green to late summer (August end) and Blue to winter (January-February) SAR images, as demonstrated in previous studies (Sood, 2015;Thakur et al, 2016Thakur et al, , 2017a. This composite image is used for SVM based supervised classification of glacier facies.…”

“…Glacier facies can be easily identified in all the SAR based temporal composites (Figure 16 to 18), with light grey, purple and blueish showing presence of percolation-freeze zone in higher, middle and lower elevations of a glacier. Green, mixed green blue showing clean or bare ice, and dark grey as dry snow zone (Patrington, 1998;Thakur et al, 2016Thakur et al, , 2017a. The SVM based supervised classification method was used to map glacier facies classes such as debris cover glacier ice, bare ice, percolation-refreeze radar zone in various elevations, wet snow and supra-glacier lakes with Sentinel-1 datasets for these glacier, with sample map shown for Gangotri glacier (Figure 18).…”

Polar Ice Sheet and Glacier Studies-Indian Efforts in last Five Years

“…All datasets were ortho-rectified with Aster GDEM (30m) in polar stereo graphic projections systems taken from Landsat 8 datasets. In first part of this work an image album has been made highlighting some of the major ice sheet features and glacier landforms present at Antarctica using ISRO's to identify additional ice sheet and glacier features which were not detected by optical data (Thakur et al, 2016). The CARTOSAT-2 high resolution images were used to identify and map some of the unique ice sheet and glacier features such as crevasses, sastrugi, nunatak, ice ridges, wind scoops, rim lines, moraines, blue ice area (BIA) and deposited snow (Fig.…”