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Retrieval of glacier ice thickness is extremely important for monitoring water resources and predicting glacier dynamics and changes. The inter-annual glacier ice thickness observations (more than 5 years) exploit the glacier mass changes. Ice thickness is one of the important parameters to predict the future sea-level rise. Without adequate knowledge and precise information of glacier ice thickness distribution, future sea-level changes cannot be accurately assessed. In this study, we use an existing flow model to estimate the ice thickness of the High Mountain Asia (HMA) glaciers, using remote sensing techniques. The glacier ice velocity is one of the significant parameters in the Laminar flow model to retrieve the ice thickness. The glacier ice velocity is derived by utilizing the Differential SAR Interferometry (DInSAR) technique. The most optimum DInSAR data (ALOS-2/PALSAR-2) is used for estimating the ice velocity of the HMA glaciers. The ice thickness is mainly estimated for five different states in the HMA region, namely Himachal Pradesh, Uttarakhand, Sikkim, Bhutan, and Arunachal Pradesh. Most of the states are observed with a mean ice thickness of 100 m. Five benchmark glaciers (Samudra Tapu, Bara Shigri, Chhota Shigri, Sakchum, and Gangotri glaciers) are also selected for validating our results with the existing thickness information. The issues related to velocity-based ice thickness inversion are also emphasized in this study. The high-velocity rate due to the influx of melting water from adjacent glaciers causes an increment in the flow rate. This abnormal velocity derives erroneous ice thickness measurements. This is one of the major problems to be considered in the velocity-based thickness-derived procedures. Finally, the investigation suggests the inclusion of the velocity influencing parameters in the physical-based models for an accurate ice thickness inversion. [ABSTRACT FROM AUTHOR]

Glacier comprises distinct features (snow, ice, and debris cover) and their identification and classification using satellite imagery is still a challenging task. Classification of different glacier features (zones) using remote sensing data is useful for numerous environmental and societal applications. The purpose of this study is to develop the fully polarimetric SAR (PolSAR) deep neural networks classification approach for the extraction of different features of the alpine glaciers. The developed approach was tested and classification results were compared with the support vector machines-based classification over the part of two glaciers: Siachen glacier and Bara Shigri glacier. The overall accuracy (OA) of GF-DNN classification is relatively high (91.17% for Siachen and 89% for Bara Shigri) with a good kappa coefficient (0.88 for Siachen and 0.85 for Bara Shigri) as compared to SVM for both the selected glaciers. An improvement of more than 10% is achieved in the OA of GF-DNN classification as compared to SVM for both the glaciers. The obtained classified results and accuracy demonstrates the potential of deep neural networks-based glacier features classification approach for glaciated terrain features. [ABSTRACT FROM AUTHOR]

Climate change is causing glaciers to retreat across much of the Himalaya, leading to a rapid shift of the vegetation cover to higher altitudes. However, the rate of vegetation shift with respect to glacier retreat, climate change, and topographic parameters is not empirically quantified. Using remote sensing measurements, we estimate (a) the rate of glacier-ice mass loss, (b) the upward vegetation line shift rate, (c) regional greening trends, and (d) a relationship between the factors influencing the greenness of the landscape and vegetation change in the Himalaya. We find that the glacier mass loss rate is 10.9 ± 1.2 Gt/yr and the mean vegetation line shifts upward in altitude by 7–28 ± 1.5 m/yr. Considering the land use/land cover change pattern, the grassland area is found to be expanding the most, particularly in the de-glaciated regions. The vegetation change is found to be controlled by soil moisture and slope of the area. [ABSTRACT FROM AUTHOR]

In this study, mass balance for Chorabari glacier of the Central Himalaya, India has been estimated. This glacier has been considered for the case study as it feeds the Mandakini River and was one of the reasons for flash floods in Rudraprayag district, Uttarakhand in 2013. The observations are based on glacier area/length change and rate of melting in the multidecade (1976-2016) using Landsat data. The study estimates an overall decrease in area at 0.8% per year. Elevation change has been studied using geodetic method utilizing shuttle radar topography mission and TanDEM-X datasets, which have shown a decrease in elevation in 16 years (2000-16). From these remotely observed parameters, a negative mass balance for the decade 2000-11 indicates glacier retreat. This study highlights the applicability of optical and radar remote sensing for the Himalayan glaciers, for better disaster management and understanding glacier dynamics in response to climate change. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Glacier velocity is one of the important parameters to know about glacier dynamics, its mass and health. Understanding glacier velocity also assists in the analysis of ice thickness, ice flux and mass balance. Furthermore, basin/sub-basin wise studies are helpful to understand the climate change over that region instead of monitoring individual glaciers. In the current study, the spatial distribution of glacier velocity is generated for the entire Chandra and Bhaga sub-basins, in the Lahaul-Spiti district of Himachal Pradesh, India, using Advanced Land Observing Satellite-2/Phased Array type L-band Synthetic Aperture Radar-2 (ALOS-2/PALSAR-2) differential interferometry pair images with a 14-days temporal gap. The glaciers in Chandra sub-basin are found to have a high flow rate as compared to the glaciers in Bhaga sub-basin. Local slope and ice thickness, which decrease towards the terminus in general, control the movement of valley glaciers, and lower movement rate is observed for most of glaciers towards the terminus/frontal area. However, a few glaciers of Bhaga sub-basin demonstrate an accelerated movement in their frontal areas. This irregular behaviour is also studied in this work and it is discovered that terrain slope and influx of melting water from adjacent glaciers are the major causes for such behaviour of these glaciers. They are, therefore, prone to accelerated mass loss compared to other glaciers in the sub-basin. Another key finding of the anomalous glacier dynamics study is the disintegrating behaviour of glaciers, which is also identified by interpreting the responses of physical scattering mechanisms retrieved from glaciers using fully polarimetric ALOS-2/PALSAR-2. Warming temperatures are expected to cause glacier retreat and separation of tributary glaciers from the main glacier body. Melt water from tributary glaciers can further accelerate glacier flow and ice melt in lower part of glacier trunk. This can lead to formation of dead ice zones and disintegration of Himalayan glaciers, which are supported by numerous tributary glaciers. Therefore, we expect that the loss in glacier area due to warming will be larger than the present prediction, where mass loss is considered from conventional way. • DInSAR glacier velocity spatial distribution is generated for Chandra and Bhaga basins, Himalaya. • Anomalous glacier dynamics information is discovered using DInSAR. • Influx of melting water from adjacent glaciers is major cause for anomalous dynamics of glaciers. • Disintegrating behaviour in glaciers is also observed due to influx of melting water. • Melt water from tributary glaciers accelerates glacier flow and bottom ice melt of glacier trunk. [ABSTRACT FROM AUTHOR]

The highly dynamic nature of snow requires frequent observations to study its various properties. Keeping this in mind, the present investigation presents results from the analysis of fully polarimetric synthetic aperture radar (POLSAR) parameters for the development of a snow depth (SD) inversion model for SD retrieval. Snow depth retrieved using ground penetrating radar (GPR) at 500 MHz over Austre Grønfjordbreen in the Svalbard region was used to understand the behaviour of certain polarimetric parameters. A significant correlation was found between field-measured SD and POLSAR parameters, namely coherence and normalized volume scattering power (R2 = 0.84 and R2 = 0.73, respectively.) Using the POLSAR scattering powers obtained from the six-component model-based decomposition (6SD), the heterogeneity and anisotropic behaviour in the firn areas are also explained. Further, based on the analyses shown in this work, a polarimetric parameter-based SD inversion algorithm have been proposed and validated. The univariate model with co-polarization coherence has the highest correlation (R2 = 0.84, Root Mean Square Error (RMSE) = 0.18). We have even tested several multivariate models for the same, to conclude that a combination of coherence, normalized volume and double-bounce scattering have a high correlation with SD (R2 = 0.84, RMSE = 0.18). Additionally, temporal and spatial variability in SD was also observed from three polarimetric SAR images acquired between 4 April 2015 and 15 May 2015 over the Western Nordenskiöld Land region. Increase in snow depth corresponding to snow precipitation events were also detected using the POLSAR data. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Himalayan glaciers have long been the focus of glaciologists across the world while trying to understand the contrasting patterns of elevation and mass changes. However, with limited number of ground observations, a comprehensive assessment of mass balance on a regional scale still remains elusive. Using the synoptic coverage of remote sensing data, we estimate a detailed spatial variation of glacier ice thickness change in the Central Himalaya of Uttarakhand using geodetic method, on a catchment scale. High resolution TerraSAR-X/TanDEM-X (12 m) and SRTM (30 m) digital elevation models (DEMs) have been utilized. The mean elevation change in the catchments is found to be −9.56 ± 0.2 m (mean annual elevation change rate is −0.68 ± 0.01 m a−1). To highlight the water potential of this region, the total ice mass loss has been estimated to be 16.0 ± 1.2 Gigatonne (Gt) from 2000–2014 from eight identified catchments namely Yamunotri, Bhagirathi, Mandakini, Alaknanda, Dhauliganga, Pindar, Goriganga and Kali/Sarda. The estimated mass balance has been validated using reported observations on five selective glaciers and the coefficient of determination is 0.93. This spatial variation of ice thickness estimated in the eight catchments is critical, as the melt-water from these glaciers contribute to the upper Ganga basin. [ABSTRACT FROM AUTHOR]

Glacier mass balance is a crucial parameter to understand the health of a glacier. The IndianHimalayas being one of the largest mountain glacier systems of the world, draws attention notonly in terms of future water potential, but also the effect it shall have on people livingdownstream upon accelerated melting. With the continuous deglaciation and retreat in mostparts of this glaciated terrain, our study focusses on the changes in mass balance over theIndian Himalayas from 2000-2014. We use geodetic method, utilizing the latestglobal digital elevation model (DEM) of TanDEM-X mission and SRTM datasetto analyze these changes. Ground observations being sparse, has been used onlyfor validation purpose. The coefficient of correlation between in-situ data and ourestimates is 0.93. It is observed that the mass balance largely varies, as we proceedfrom the extreme end of the Karakoram Himalayas (in the west) towards the eastin Arunachal Pradesh. This has been attributed to the variability in the regionalclimatic conditions and changing geomorphology of the glaciers. The total massbalance change in the Indian Himalayas has been estimated to be - 4.7 ± 1.2 Gt yr−1. This study not only highlights the water lost in the Indian Himalayas which potentiallyincreases our dependence on the seasonal precipitated water, but also portrays the potential ofthe newly released TanDEM-X DEM to monitor such dynamic systems like the mountainglaciers. [ABSTRACT FROM AUTHOR]