Glacier velocity is one of the most important parameters to understand glacier dynamics. The Severnaya Zemlya archipelago is host to many glaciers of which four major ice caps encompassing these glaciers are studied, namely, Academy of Sciences, Rusanov, Karpinsky, and University. In this study, we adopted the differential interferometric synthetic aperture radar (DInSAR) method utilizing ALOS-2/PALSAR-2 datasets, with a temporal resolution of 14 days. The observed maximum velocity for one of the marine-terminating glaciers in the Academy of Sciences Ice Cap was 72.24 cm/day (≈263 m/a). For the same glacier, an increment of 3.75 times the flow rate was observed in 23 years, compared to a previous study. This has been attributed to deformation in the bed topography of the glacier. Glaciers in other ice caps showed a comparatively lower surface velocity, ranging from 7.43 to 32.12 cm/day. For estimating the error value in velocity, we selected three ice-free regions and calculated the average value of their observed movement rates by considering the fact that there is zero movement for ice-free areas. The average value observed for the ice-free area was 0.09 cm/day, and we added this value in our uncertainty analysis. Further, it was observed that marine-terminating glaciers have a higher velocity than land-terminating glaciers. Such important observations were identified in this research, which are expected to facilitate future glacier velocity studies.

Differential SAR Interferometry (DInSAR) is the process of differencing two Interferograms for measuring surface movement with an accuracy of millimeter range. The DInSAR process can be applied to observe glacier movement, earthquake deformations, volcanic activities and rate of subsidence or uplift caused due to the extraction of groundwater or coal. By using single pass interferometry technique we can also generate accurate DEM. In this paper, we are presenting the movement of a Chhota Shigri glacier with the help two pass DInSAR technique and mainly we concentrated on the optimum conditions for estimating glacier movement using DInSAR. We got good coherence and Interferogram fringes for L-band sensor with less temporal baseline. Therefore, we generated glacier velocity using ALOS-2 data with 14 days temporal baseline. Initially, we generated Interferogram (defo-pair) by taking 10th March 2015 image as a master and 24th March 2015 image as a slave. But this generated Interferogram also having topographic information and atmospheric errors with the displacement component. Therefore, we used SRTM DEM for removing topographic information from the Interferogram. Because we are using L-band data, results may not be affected by troposphere. Maximum glacier velocity we observed in the accumulation zone as 7.285 cm/day in the month of March and while it’s moving towards ablation zone the glacier velocity is decreasing.

Glacier velocity is an important parameter to characterize glacier dynamics and to derive ice thickness and mass balance. The 2-pass/3-pass Differential Synthetic Aperture Radar Interferometry (DInSAR) techniques are advantageous in estimating glacier movements. However, the 2-pass DInSAR requires an external Digital Elevation Model (DEM), whereas the 3-pass DInSAR does not. The 3-pass DInSAR technique is adopted with Sentinel-1A/1B to map the Svalbard glacier flow velocities. Furthermore, the effect of glacier surface elevation change on the 2-pass DInSAR results were revealed by comparing glacier velocity with the two time period topographic information. The coherence indicates that Sentinel-1A/1B has a high potential to infer operational glacier velocity using the 3-pass DInSAR method with an average atmospheric uncertainty of 0.24 cm/day over the studied region. The precision of the 3-pass DInSAR is analyzed by comparing 2-pass derived line-of-sight (LOS) velocity on the same dates. The 3-pass DInSAR achieves high-resolution and detailed information.

This study uses time-series L-band ALOS-2/PALSAR-2 and C-band Sentinel-1 data to study the change in backscatter values due to deforestation and regrowth in a plantation forest situated at Uttarakhand, India. The data were acquired between 2014 and 2018. The trend in the SAR backscatter due to harvest of plantation forest and regrowth of secondary vegetation is analyzed. The results show that the L-band SAR backscatter is sensitive to forest loss, while the C-band SAR backscatter showed high sensitivity to forest regeneration. The results emphasize the requirement of continuous L-band acquisitions for forest monitoring activities.