Extraction of glacier surface elevation and velocity in high Asia with ERS-1/2 Tandem SAR data: Application to Puruogangri ice field, Tibetan Plateau

Our understanding of identifying and monitoring surge-type glacier distribution patterns, fluctuations, periodicities, and occurrence mechanism under the changing climate is challenging and scarce due to small numbers, limitations on the spatiotemporal coverage of remote sensing observations, and insufficient field-based glaciological data from the High Mountain Asia. The surging glaciers have caused major hazards, and their movement can destroy peripheral and downstream areas like roads, connecting bridges, villages, and hydropower stations and trigger a glacial lake outburst flood or form a dammed (moraine or ice) lake in High Mountain Asia (HMA) in the recent past. Many glaciers have experienced a mass loss and retreat due to ongoing climate change in HMA in recent decades, whereas studies conducted in the Karakorum, Pamir, Tien Shan, and Kunlun Shan regions have reported the surging of the glaciers. Whereas, in the central Himalayan region, very limited studies have been able to identify and explain in detail the surging glaciers and their surge mechanism. In this study, we identified an unnamed glacier surge in the central Himalaya, triggered between 12 September and 14 October 2019 (on a monthly scale) using multi-source high-resolution remote sensing data (CARTOSAT-1 [2011 and 2012], LISS-IV-2A [2011, 2017, and 2020], Landsat-5 [TM], 7 [ETM +], 8 [OLI/TIRS], and Sentinel [2A and 2B]) in conjunction with shuttle radar topography mission [SRTM], Advanced Spaceborne Thermal Emission and Reflection Radiometer [ASTER], and High Mountain Asia digital elevation model (DEM) database. We used a series of algorithms package named MicMac ASTER (MMASTER) tool for generating DEMs from data of two telescopes for the estimation of the surface elevation change, and to calculate the surface velocity, we employed the "Co-registration of Optically Sensed Images and Correlation" (COSI-Corr), a Fourier-based, highly advanced matching program. Based on the observations of the glacier terminus fluctuation, surface velocity, and surface elevation change from 1993 to 2022, this study revealed that the unnamed glacier underwent a surge for the first time in the past three decades. The glacier's surface velocity increased from 7 ± 3 m year-1 during quiescence (2001-2002) to 163 ± 1 m year-1 during the surge (2019-2020) and then decreased to 17 ± 2 m year-1 between 2021 and 2022. Between 12 September and 14 October 2019, there was a sudden and significant increase in surface velocity of 863m within a month (i.e., 27 m/day compared to the month prior), indicating the initiation of the surge. Overall, the present study results suggest that the glacier's velocity varied considerably during the observed period, with periods of gradual increase, sudden increase, and subsequent decrease. Further, the changes in glacier surface suggest a total mean elevation change of 0.26 ± 0.2 m year-1 between 2000 and 2020. In this study, we present novel observations of a glacier surge in the central Himalaya, compare its characteristics to surge-type glaciers reported elsewhere, and discuss the possible mechanisms controlling its behavior.

Monitoring glacier flow is vital to understand the response of mountain glaciers to environmental forcing in the context of global climate change. Seasonal and interannual variability of surface velocity in the temperate glaciers of the Parlung Zangbo Basin (PZB) has attracted significant attention. Detailed patterns in glacier surface velocity and its seasonal variability in the PZB are still uncertain, however. We utilized Landsat-8 (L8) OLI data to investigate in detail the variability of glacier velocity in the PZB by applying the normalized image cross-correlation method. On the basis of satellite images acquired from 2013 to 2020, we present a map of time-averaged glacier surface velocity and examined four typical glaciers (Yanong, Parlung No.4, Xueyougu, and Azha) in the PZB. Next, we explored the driving factors of surface velocity and of its variability. The results show that the glacier centerline velocity increased slightly in 2017–2020. The analysis of meteorological data at two weather stations on the outskirts of the glacier area provided some indications of increased precipitation during winter-spring. Such increase likely had an impact on ice mass accumulation in the up-stream portion of the glacier. The accumulated ice mass could have caused seasonal velocity changes in response to mass imbalance during 2017–2020. Besides, there was a clear winter-spring speedup of 40% in the upper glacier region, while a summer speedup occurred at the glacier tongue. The seasonal and interannual velocity variability was captured by the transverse velocity profiles in the four selected glaciers. The observed spatial pattern and seasonal variability in glacier surface velocity suggests that the winter-spring snow might be a driver of glacier flow in the central and upper portions of glaciers. Furthermore, the variations in glacier surface velocity are likely related to topographic setting and basal slip caused by the percolation of rainfall. The findings on glacier velocity suggest that the transfer of winter-spring accumulated ice triggered by mass conservation seems to be the main driver of changes in glacier velocity. The reasons that influence the seasonal surface velocity change need further investigation.

The Mt.Tomur glaciers, in the Tian Shan mountains of Western China, are usually debris-covered, and due to climate change, glacial hazards are becoming more frequent in this region. However, no changes in the long-time series of glacier surface velocities have been observed in this region. Conducting field measurements in high-altitude mountains is relatively difficult, and consequently, the dynamics and driving factors are less studied. Here, image-correlation offset tracking using Landsat images was exploited to estimate the glacier surface velocity of glaciers in the Mt.Tomur region from 2000 to 2020 and to assess glacier ice thickness. The results show that the glacier surface velocity in the Mt.Tomur region showed a significant slowdown during 2000–2020, from 6.71 ± 0.66 m a−1 to 3.95 ± 0.66 m a−1, an overall decrease of 41.13%. The maximum glacier ice thickness in the Mt.Tomur region was estimated based on the ice flow principle being 171.27 ± 17.10 m, and the glacier average thickness is 50.00 ± 5.0 m. Glacier thickness at first increases with increasing altitude, showing more than 100 ± 10 m ice thickness between 3400 m and 4300 m, and then decreases with further increases in altitude. The reliability of the surface velocity and ice thickness obtained from remote sensing was proved using the measured surface velocity and ice thickness of Qingbingtan glacier No. 72 stall (the correlation coefficient R2 > 0.85). The debris cover has an overall mitigating effect on the ablation and movement rate of Qingbingtan Glacier No. 72; however, it has an accelerating effect on the ablation and movement rate of glacier No. 74.

Glacier evolution with time provides important information about climate variability. Here, we investigated glacier velocity changes in the Himalayas and analysed the patterns of glacier flow. We collected 220 scenes of Landsat-7 panchromatic images between 1999 and 2000, and Sentinel-2 panchromatic images between 2017 and 2018, to calculate surface velocities of 36,722 glaciers during these two periods. We then derived velocity changes between 1999 and 2018 for the early winter period, based on which we performed a detailed analysis of motion of each individual glacier, and noted that the changes are spatially heterogeneous. Of all the glaciers, 32% have sped up, 24.5% have slowed down, and the rest 43.5% have remained stable. The amplitude of glacier slowdown, as a result of glacier mass loss, is significantly larger than that of speedup. At regional scales, we found that glacier surface velocity in winter has uniformly decreased in the western part of the Himalayas between 1999 and 2018, while increased in the eastern part; this contrasting difference may be associated with decadal changes in accumulation and/or melting under different climatic regimes. We also found that the overall trend of surface velocity exhibits seasonal variability: summer velocity changes are positively correlated with mass loss, i.e., velocity increases with increasing mass loss, whereas winter velocity changes show a negative correlation. Our study suggests that glacier velocity changes in the Himalayas are spatially and temporally heterogeneous, in agreement with studies that previously highlighted this trend, emphasising complex interactions between glacier dynamics and environmental forcing.

High-resolution monitoring of debris-covered glacier mass budget and flow velocity using repeated UAV photogrammetry in Iran

The velocity of glacier is the most important parameter in the study of glaciers and remote sensing is a powerful tool to calculate their surface velocities. Due to persistent cloud cover in this region, it is impossible to acquire enough optical images to provide measurements. However, measurement of the offsets between two SAR images is an effective way to determine surface velocity. In order to do this, offsets both in slant range and azimuth directions are derived from two SAR images. The movement of the glacier during the SAR data acquisition time is calculated after the global part of offsets has been removed by the polynomial fit method. The offsets used for removing the global part are selected on the basis of the Single-to-Noise ratio (SNR) and correlation in area without glaciers but with large topographic changes. The surface velocity of the whole glacier using SAR data will make a significant contribution to the study of glacier dynamics. The Kekesayi glacier can be divided into four parts, based on the velocity map. The results show that the surface velocity of the Kekesayi glacier is different on the different part of the glacier, and offset measurements are an effective method for the study of glaciers.

Unmanned Aerial Vehicles (UAVs) are being increasingly used in glaciology demonstrating their potential for the generation of high-resolution digital elevation models (DEMs) that can be further used for the evaluation of glacial processes in detail. Such investigations are especially important for the evaluation of surface changes of small valley glaciers, which are not well-represented in lower-resolution satellite-derived products. In this study, we performed two UAV surveys at the end of the ablation season in 2019 and 2021 on Waldemarbreen, a High-Arctic glacier in NW Svalbard. We derived the mean annual glacier surface velocity of 5.3 m. The estimated mean glacier surface elevation change from 2019 to 2021 was −1.46 m a−1 which corresponds to the geodetic mass balance (MB) of −1.33 m w.e. a−1. The glaciological MB for the same period was −1.61 m w.e. a−1. Our survey includes all Waldemarbreen and demonstrates the efficiency of high-resolution DEMs produced from UAV photogrammetry for the reconstruction of changes in glacier surface elevation and velocity. We suggest that glaciological and geodetic MB methods should be used complementary to each other.

Glacier surging is a dynamic instability that affects the flow of some glaciers, modifying the glacier area, surface velocity, and surface elevation. It is also among the major causes of ice dams and glacier lake floods. Previous studies have shown that in the West Kunlun Mountains| (WKM) where a cluster of surge‐type glaciers had been found, the glaciers were relatively stable in recent years. Nevertheless, the surge cycle and its impact on glacier changes on a regional scale are poorly understood. In this study, we updated the surge‐type glacier inventory of the WKM using the detailed changes in glacier length, surface velocity, and surface elevation during the 1972–2020 period using 78 Landsat optical images, 86 Sentinel‐1 synthetic aperture radar (SAR) images, and three digital elevation models of the WKM. The updated results show that among the 423 glaciers in the WKM, 10 are confirmed as surge‐type glaciers, three are likely surge‐type glaciers, and five are possible surge‐type glaciers. Furthermore, these 18 glaciers account for 63% of the total glacier area. During the period analyzed, there were marked changes in the lengths, areas and surface elevations of all surge‐type glaciers, while those of the non‐surge‐type glaciers were relatively stable. These results appear to indicate that the observed regional trends of glaciers in the WKM recently may be related to the existence of surge‐type glaciers. Furthermore, the surge‐type glacier underwent advance after accelerating for 3–4 years, which could be used to forecast when glacier termini may advance and avoid the possible catastrophic damages.

Most glaciers on the Tibetan Plateau have experienced continuous mass losses in response to global warming. However, the seasonal dynamics of glaciers on the southeastern Tibetan Plateau have rarely been reported in terms of glacier surface elevation and velocity. This paper presents a first attempt to explore the seasonal dynamics of the debris-covered Dagongba Glacier within the southeastern Tibetan Plateau. We use the multitemporal unoccupied aerial vehicle images collected over the lower ablation zone on 8 June and 17 October 2018, and 13 May 2019, and then perform an analysis concerning climatic fluctuations. The results reveal that the mean surface elevation decrease of the Dagongba Glacier during the warm season ($2.81\pm 0.44$ m) was remarkably higher than the cold season ($0.72\pm 0.45$ m). Particularly notable glacier surface elevation changes were found around supraglacial lakes and ice cliffs where ice ablation rates were $\sim$3 times higher than the average. In addition, a larger longitudinal decline of glacier surface velocity was observed in the warm season than that in the cold season. In terms of further comparative analysis, the Dagongba Glacier experienced a decrease in surface velocity between 1982–83 and 2018–19, with a decrease in the warm season possibly twice as large as that in the cold season.

Glacier evolution with time provides important information about climate variability. Here we investigate glacier surface velocity in the Himalayas and analyse the patterns of glacier flow. We collect 220 scenes of Landsat-7 panchromatic images between 1999 and 2000, and Sentinel-2 panchromatic images between 2017 and 2018, to calculate surface velocities of 36,722 glaciers during these two periods. We then derive velocity changes between 1999 and 2018, based on which we perform a detailed analysis of motion of each individual glacier, and noted that the changes are spatially heterogeneous. Of all the glaciers, 32 % have speeded up, 24.5 % have slowed down, and the rest 43.5 % remained stable. The amplitude of glacier slowdown, as a result of glacier mass loss, is remarkably larger than that of speedup. At regional scales, we found that glacier surface velocity in winter has uniformly decreased in the western part of the Himalayas between 1999 and 2018, whilst increased in the eastern part; this contrasting difference may be associated with decadal changes in accumulation and/or melting under different climatic regimes. We also found that the overall trend of surface velocity exhibits seasonal variability: summer velocity changes are positively correlated with mass loss, whereas winter velocity changes show a negative correlation. Our study suggests that glacier velocity changes in the Himalayas are more spatially and temporally heterogeneous than previously thought, emphasising complex interactions between glacier dynamics and environmental forcing.

Glacier evolution with time provides important information about climate variability. Here we investigate glacier surface velocity in the Himalayas and analyse the patterns of glacier flow. We collect 220 scenes of Landsat-7 panchromatic images between 1999 and 2000, and Sentinel-2 panchromatic images between 2017 and 2018, to calculate surface velocities of 36,722 glaciers during these two periods. We then derive velocity changes between 1999 and 2018, based on which we perform a detailed analysis of motion of each individual glacier, and noted that the changes are spatially heterogeneous. Of all the glaciers, 32 % have speeded up, 24.5 % have slowed down, and the rest 43.5 % remained stable. The amplitude of glacier slowdown, as a result of glacier mass loss, is remarkably larger than that of speedup. At regional scales, we found that glacier surface velocity in winter has uniformly decreased in the western part of the Himalayas between 1999 and 2018, whilst increased in the eastern part; this contrasting difference may be associated with decadal changes in accumulation and/or melting under different climatic regimes. We also found that the overall trend of surface velocity exhibits seasonal variability: summer velocity changes are positively correlated with mass loss, whereas winter velocity changes show a negative correlation. Our study suggests that glacier velocity changes in the Himalayas are more spatially and temporally heterogeneous than previously thought, emphasising complex interactions between glacier dynamics and environmental forcing.

<p>Climate induced glacier change has important implications for global sea level rise, freshwater availability and geomorphologic hazards. Changes in ice dynamics and mass flow can globally be observed by long- and short-term changes in ice surface velocity. Consistent and continuous data on glacier surface velocity are important inputs to time series analyses, numerical ice dynamic modelling and glacier mass balance calculations. Therefore, glacier surface velocities have been identified as an Essential Climate Variable (ECV) that should be monitored on a regular and global scale. Since 2014, repeat-pass Synthetic Aperture Radar (SAR) data, acquired by the Sentinel-1 constellation as part of ESA’s (European Space Agency) Copernicus program, enable global, near real time-like and fully automatic processing of glacier velocity fields at up to 6-day temporal resolution, independent of weather conditions, season and daylight.</p><p>We present a new near-global data set of Sentinel-1 glacier velocities that comprises continuously updated image pair velocity fields, as well as monthly and annually averaged velocity mosaics at 200 m spatial resolution, derived from applying intensity feature tracking on both archived and new acquisitions. The data set covers all major glaciated regions outside the polar ice sheets and is generated in an HPC (High Performance Computing) environment at the University of Erlangen-Nuremberg. By the beginning of January 2021, we processed more than 110.000 Sentinel-1 scenes, amounting to roughly 450 TB of data. The velocity products are freely accessible via an interactive web portal (http://retreat.geographie.uni-erlangen.de) that provides capabilities for download and simple online analyses. We give information on the procedures of data generation, as well as on how to access the data and demonstrate the capabilities of our products for velocity time series analyses at very high temporal resolution. We compare our data to velocity products generated from very high resolution TerraSAR-X SAR (Synthetic Aperture Radar) and Landsat-8 optical (ITS_LIVE, GoLIVE) data. For this comparison we selected Svalbard as an example region, as it includes glaciers of a broad variety of sizes, different velocitiy magnitudes and seasonal velocity patterns, as well as very fast flowing surging glaciers and almost featureless ice caps.</p>

Gangotri glacier dynamics from multi-sensor SAR and optical data

This study analyses spatially resolved estimates of mass budget and surface velocity of glaciers in the Zanskar Basin of Western Himalaya in the context of varying debris cover, glacier hypsometry and orientation. The regional glacier mass budget for the period of 1999–2014 is −0.38 ± 0.09 m w.e./a. Individual mass budgets of 10 major glaciers in the study area varied between −0.13 ± 0.07 and −0.66 ± 0.09 m w.e./a. Elevation changes on debris-covered ice are considerably less negative than over clean ice. At the same time, glaciers having >20% of their area covered by debris have more negative glacier-wide mass budgets than those with <20% debris cover. This paradox is likely explained by the comparatively larger ablation area of extensively debris-covered glaciers compared to clean-ice glaciers, as indicated by hypsometric analysis. Additionally, surface velocities computed for the 2013–14 period reveal near stagnant debris-covered snouts but dynamically active main trunks, with maximum recorded velocity of individual glaciers ranging between ~50 ± 5.58 and ~90 ± 5.58 m/a. The stagnant debris-covered extent, which varies from glacier-to-glacier, are also characterized by ice cliffs and melt ponds that appreciably increase the overall surface melting of debris-covered areas.

The situation of stable and slightly advancing glaciers in the Karakoram is called the “Karakoram anomaly”. Glacier surface velocity is one of the key parameters of glacier dynamics and mass balance, however, the response of glacier motion to this regional anomaly is not fully understood. Here, we characterize the spatial-temporal variations in glacier velocity over the Central Karakoram from 1999–2003. The inter-annual glacier velocity fields were retrieved using a cross-correlation-based algorithm applied to four Landsat-7 Enhanced Thematic Mapper Plus (ETM+) panchromatic image pairs. We find that most of the glaciers on the southern slope flowed faster than those on the northern slope, which might be attributed to the differences in glacier sizes. Furthermore, ice motion observations over four years reveal that most of the glaciers were quasi-stable or experienced small fluctuations of flow velocity during our study period. We identify a new surging event for the South Skamri Glacier in the study period by investigating the glacier frontal changes and the longer-term time series of surface velocities between 1996 and 2006. From the transverse velocity profiles of seven typical glaciers, we infer that basal sliding is the predominant motion mechanism of the middle and upper glaciers, whereas internal deformation dominates closest to the glacier terminus.