Glacier surface velocity estimation in the West Kunlun Mountain range from L-band ALOS/PALSAR images using modified synthetic aperture radar offset-tracking procedure

Changes in ice velocity of a glacier regulate its mass balance and dynamics. The estimation of glacier flow velocity is therefore an important aspect of temporal glacier monitoring. The utilisation of conventional ground-based techniques for detecting glacier surface flow velocity in the rugged and alpine Himalayan terrain is extremely difficult. Remote sensing-based techniques can provide such observations on a regular basis for a large geographical area. Obtaining freely available high quality remote sensing data for the Himalayan regions is challenging. In the present work, we adopted a differential band composite approach, for the first time, in order to estimate glacier surface velocity for non-debris and supraglacial debris covered areas of a glacier, separately. We employed various bandwidths of the Landsat 8 data for velocity estimation using the COSI-Corr (co-registration of optically sensed images and correlation) tool. We performed the accuracy assessment with respect to field measurements for two glaciers in the Indian Himalaya. The panchromatic band worked best for non-debris parts of the glaciers while band 6 (SWIR – short wave infrared) performed best in case of debris cover. We correlated six temporal Landsat 8 scenes in order to ensure the performance of the proposed algorithm on monthly as well as yearly timescales. We identified sources of error and generated a final velocity map along with the flow lines. Over- and underestimates of the yearly glacier velocity were found to be more in the case of slow moving areas with annual displacements less than 5 m. Landsat 8 has great capabilities for such velocity estimation work for a large geographic extent because of its global coverage, improved spectral and radiometric resolutions, free availability and considerable revisit time.

Download Full-text

Glacier surface velocity estimation using stokes vector correlation

2015 IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) ◽

10.1109/apsar.2015.7306281 ◽

2015 ◽

Author(s):

Arnab Muhuri ◽

Avik Bhattacharya ◽

Ryo Natsuaki ◽

Akira Hirose

Keyword(s):

Velocity Estimation ◽

Surface Velocity ◽

Stokes Vector ◽

Glacier Surface ◽

Vector Correlation

Download Full-text

Glacier surface velocity estimation using SAR interferometry technique applying ascending and descending passes in Himalayas

International Journal of Applied Earth Observation and Geoinformation ◽

10.1016/j.jag.2011.02.004 ◽

2011 ◽

Vol 13 (4) ◽

pp. 545-551 ◽

Cited By ~ 48

Author(s):

V. Kumar ◽

G. Venkataramana ◽

K.A. Høgda

Keyword(s):

Velocity Estimation ◽

Sar Interferometry ◽

Surface Velocity ◽

Glacier Surface

Download Full-text

Seasonal Surface Change of Urumqi Glacier No. 1, Eastern Tien Shan, China, Revealed by Repeated High-Resolution UAV Photogrammetry

Remote Sensing ◽

10.3390/rs13173398 ◽

2021 ◽

Vol 13 (17) ◽

pp. 3398

Author(s):

Puyu Wang ◽

Hongliang Li ◽

Zhongqin Li ◽

Yushuo Liu ◽

Chunhai Xu ◽

...

Keyword(s):

Tien Shan ◽

Surface Elevation ◽

Surface Velocity ◽

Elevation Change ◽

The West ◽

Glacier Surface ◽

Surface Change ◽

Ablation Area ◽

Glacier Terminus ◽

Surface Changes

The seasonal surface changes of glaciers in Tien Shan have seen little prior investigation despite the increase in geodetic studies of multi-year changes. In this study, we analyzed the potential of an Unmanned Aerial Vehicle (UAV) to analyze seasonal surface change processes of the Urumqi Glacier No. 1 in eastern Tien Shan. We carried out UAV surveys at the beginning and the end of the ablation period in 2018. The high-precision evolution of surface elevation, geodetic mass changes, surface velocity, and terminus change in the surveyed ablation area were correspondingly derived in combination with ground measurements, including stake/snow-pit observation and GPS measurement. The derived mean elevation change in the surveyed ablation area was −1.64 m, corresponding to the geodetic mass balance of approximately −1.39 m w.e. during the ablation period in 2018. The mean surface velocity was 3.3 m/yr and characterized by the spatial change of the velocity, which was less in the East Branch than in the West Branch. The UAV survey results were a little less than those from the ground measurements, and the correlation coefficient was 0.88 for the surface elevation change and 0.87 for surface displacement. The relative error of the glacier terminus change was 4.5% for the East Branch and 6.2% for the West Branch. These results show that UAV photogrammetry is ideal for assessing seasonal glacier surface changes and has a potential application in the monitoring of detailed glacier changes.

Download Full-text

Surface Velocity Analysis of Surge Region of Karayaylak Glacier from 2014 to 2020 in the Pamir Plateau

Remote Sensing ◽

10.3390/rs13040774 ◽

2021 ◽

Vol 13 (4) ◽

pp. 774

Author(s):

Yanfei Peng ◽

Zhongqin Li ◽

Chunhai Xu ◽

Hui Zhang ◽

Weixiao Han

Keyword(s):

Accuracy Assessment ◽

Meteorological Data ◽

Maximum Velocity ◽

Google Earth ◽

Meteorological Station ◽

Surface Velocity ◽

Control Mechanisms ◽

The West ◽

Glacier Surface ◽

Study Region

The west branch of Karayaylak Glacier (eastern Pamir Plateau) surged in May 2015, significantly impacting on local socio-economic development. This event was also of great significance for studies of surging glaciers. Using Sentinel-1 imagery analyzed by offset tracking, based on normalized cross-correlation (NCC), and with the support of the Google Earth Engine (GEE) platform, we quantified the ice surface velocity of the west branch and terminus of Karayaylak Glacier from 13 October 2014 to 17 October 2020. Sentinel-1 images were acquired at intervals of 12 or 24 days. We also used a three-dimensional (3-D) laser scanner to measure the velocity of 3 ablation stakes and 56 feature points in the study region from 15 August to 6 October 2015, for the purpose of accuracy assessment. We set up an automatic meteorological station to record the air temperature in the same period and combined this with data from Tashkurgan meteorological station from 1957 to 2015. Analysis of this dataset provided insights into the glacier surge mechanism, with the following conclusions. (1) Surface velocity of the west branch and terminus of Karayaylak Glacier increased sharply after October 2014. The velocity then dropped significantly in the two months after the surge, and stayed at low values for nearly a year. After 2017, the velocity was slightly higher than in the previous period. (2) The surge event occurred from 11 April to 17 May 2015; the average surface velocity in this phase attained 2395 m a−1 with a maximum velocity of 4265 m a−1 at the west branch terminus. (3) From 2017 to 2020, the velocity showed periodic annual changes. (4) Based on the meteorological data analysis, we conclude that this surge resulted from the interaction between thermal and hydrological control mechanisms. Simultaneously, we demonstrate the high potential of the GEE platform and Sentinel-1 data to extract glacier surface velocity.

Download Full-text

Area and Mass Changes of Glaciers in the West Kunlun Mountains Based on the Analysis of Multi-Temporal Remote Sensing Images and DEMs from 1970 to 2018

Remote Sensing ◽

10.3390/rs12162632 ◽

2020 ◽

Vol 12 (16) ◽

pp. 2632

Author(s):

Bo Cao ◽

Weijin Guan ◽

Kaiji Li ◽

Zhenling Wen ◽

Hui Han ◽

...

Keyword(s):

Stable State ◽

Series Data ◽

Remote Sensing Images ◽

The West ◽

Glacier Surface ◽

Kunlun Mountains ◽

Surface Elevation Change ◽

Recent Climate ◽

Multi Temporal ◽

West Kunlun

Most of the world’s glaciers have retreated significantly against the background of recent climate warming, while reports have indicated that the glaciers in the West Kunlun Mountains (WKL) may be in a relatively stable state, although there are some gaps in previous research. Based on Landsat series data, topographic maps, SRTM and TanDEM-x data, this paper extracts detailed glacial area information and glacial mass balance during different time periods from 1970 to 2018. We found that, the total area of glaciers in the WKL decreased by 8.0 km2 from 1972 to 2018. The area decreased by 12.0 km2 from 1972 to 1991 and increased by 4.7 km2 from 2010 to 2018. Glacier surface elevation change results in the WKL showed that the overall glacier thickness slightly decreased from 1970 to 2016, with an average of 1.9 ± 1.0 m. The glaciers thinned by approximately 2.5 ± 1.0 m from 1970 to 2000, while from 2000 to 2016, the glaciers thickened approximately by 0.6 ± 1.0 m. Overall, the glaciers in the WKL showed very slight retreat. In addition, the mass changes of glaciers were affected by glacial surging.

Download Full-text

Temporal Multi-Looking of SAR Image Series for Glacier Velocity Determination and Speckle Reduction

10.5194/egusphere-egu2020-3643 ◽

2020 ◽

Author(s):

Silvan Leinss ◽

Shiyi Li ◽

Philipp Bernhard ◽

Othmar Frey

Keyword(s):

High Resolution ◽

Velocity Field ◽

Cross Correlation ◽

Surface Velocity ◽

Sar Image ◽

Sar Images ◽

Glacier Surface ◽

Radar Images ◽

Glacier Velocity ◽

Offset Tracking

The velocity of glaciers is commonly derived by offset tracking using pairwise cross correlation or feature matching of either optical or synthetic aperture radar (SAR) images.&#160; SAR images, however, are inherently affected by noise-like radar speckle and require therefore much larger images patches for successful tracking compared to the patch size used with optical data. As a consequence, glacier velocity maps based on SAR offset tracking have a relatively low resolution compared to the nominal resolution of SAR sensors. Moreover, tracking may fail because small features on the glacier surface cannot be detected due to radar speckle. Although radar speckle can be reduced by applying spatial low-pass filters (e.g. 5x5 boxcar), the spatial smoothing reduces the image resolution roughly by an order of magnitude which strongly reduces the tracking precision. Furthermore, it blurs out small features on the glacier surface, and therefore tracking can also fail unless clear features like large crevasses are visible.In order to create high resolution velocity maps from SAR images and to generate speckle-free radar images of glaciers, we present a new method that derives the glacier surface velocity field by correlating temporally averaged sub-stacks of a series of SAR images. The key feature of the method is to warp every pixel in each SAR image according to its temporally increasing offset with respect to a reference date. The offset is determined by the glacier velocity which is obtained by maximizing the cross-correlation between the averages of two sub-stacks. Currently, we need to assume that the surface velocity is constant during the acquisition period of the image series but this assumption can be relaxed to a certain extend.As the method combines the information of multiple images, radar speckle are highly suppressed by temporal multi-looking, therefore the signal-to-noise ratio of the cross-correlation is significantly improved. We found that the method outperforms the pair-wise cross-correlation method for velocity estimation in terms of both the coverage and the resolution of the velocity field. At the same time, very high resolution radar images are obtained and reveal features that are otherwise hidden in radar speckle.As the reference date, to which the sub-stacks are averaged, can be arbitrarily chosen a smooth flow animation of the glacier surface can be generated based on a limited number of SAR images. The presented method could build a basis for a new generation of tracking methods as the method is excellently suited to exploit the large number of emerging free and globally available high resolution SAR image time series.

Download Full-text

SEASONAL COMPARISON OF VELOCITY OF THE EASTERN TRIBUTARY GLACIERS, AMERY ICE SHELF, ANTARCTICA, USING SAR OFFSET TRACKING

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-2-w5-595-2019 ◽

2019 ◽

Vol IV-2/W5 ◽

pp. 595-600

Author(s):

S. D. Jawak ◽

S. Kumar ◽

A. J. Luis ◽

P. H. Pandit ◽

S. F. Wankhede ◽

...

Keyword(s):

Primary Objective ◽

Velocity Estimation ◽

East Antarctica ◽

Surface Velocity ◽

Ice Shelf ◽

Ice Shelves ◽

Tracking Method ◽

Amery Ice Shelf ◽

Glacier Velocity ◽

Offset Tracking

Abstract. Antarctica and Greenland are two major Earth’s continental ice shelves which play an important role in influencing Earth’s energy balance through their high albedo. The ice sheets comprise of grounded ice or the continental glaciers and their associated ice shelves. Surface velocity is an important parameter that needs to be monitored to understand the glacier dynamics. Marine terminating glaciers have higher velocity than land terminating glaciers. Therefore, ice shelves are generally observed to have higher velocity as compared to continental glaciers. The focus of this study is Amery ice shelf (AIS) which is the third largest ice shelf located in east Antarctica terminating into the Prydz Bay on the eastern Antarctica. The surface ice-flow velocity of AIS is very high compared to its surrounding glaciers which flows at a rate of 1400&thinsp;m&thinsp;a&minus;1 and drains about 8% of the Antarctic ice sheet. AIS is fed by different glaciers and ice streams at the head, as well as from the western and eastern side of the ice shelf before it terminates into the ocean. The primary objective of this study was to compute velocity of the eastern tributary glaciers of AIS using SAR from Sentinel-1 data. The secondary objective was to compare the winter and summer velocities of the glaciers for 2017&ndash;2018. The offset tracking method has been applied to the ground range detected (GRD) product obtained from Sentinel-1 satellite. This method is suitable for regions with higher glacier velocity where interferometry is generally affected by the loss of coherence. The offset tracking method works by tracking the features on the basis of another feature and calculates the offset between the two features in the images. Two tributary glaciers near the Clemence massif and another glacier near the Pickering Nunatak feed into this ice shelf from the eastern glacial basin region that drains ice from the American Highland, east Antarctica. The glaciers near the Clemence massif showed low annual velocity which ranged from 100&thinsp;m&thinsp;a&minus;1 at the head to &sim;300&thinsp;m&thinsp;a&minus;1 near the end of the glacier, where it merges with AIS. The glaciers flowing near the Pickering Nunatak exhibited moderate velocity ranging from 150&thinsp;m&thinsp;a&minus;1 at its head and reaching up to 450&thinsp;m&thinsp;a&minus;1 near the tongue. The summer velocity (March 2018) was observed to be higher than the velocity in winter (July 2017) and the difference between the summer and the winter velocities was found to be between 50&thinsp;m&thinsp;a&minus;1 and 130&thinsp;m&thinsp;a&minus;1. The results for the velocity were obtained at 120&thinsp;m resolution and were compared with the previous MEaSUREs (Making Earth System Data Records for Use in Research Environments) yearly velocity at 450&thinsp;m and 1&thinsp;km resolution provided by National Snow and Ice Data Center portal. The results were evaluated using statistical measure- bias and the accuracy was derived using the root mean square error. The bias did not exceed 20&thinsp;m&thinsp;a&minus;1 for the three glaciers and the accuracy was observed to be more than 85% for most of the regions. The accuracy of the results suggests that the offset tracking technique is useful for future velocity estimation in the regions of high glacier velocity.

Download Full-text

ESTIMATION OF SHIE GLACIER SURFACE MOVEMENT USING OFFSET TRACKING TECHNIQUE WITH COSMO-SKYMED IMAGES

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-2-w4-493-2017 ◽

2017 ◽

Vol IV-2/W4 ◽

pp. 493-497

Author(s):

Q. Wang ◽

W. Zhou ◽

J. Fan ◽

W. Yuan ◽

H. Li ◽

...

Keyword(s):

High Resolution ◽

Maximum Velocity ◽

Weather Conditions ◽

Synthetic Aperture ◽

Sar Images ◽

Glacier Surface ◽

Surface Movement ◽

Tracking Technique ◽

Offset Tracking ◽

Near Future

Movement is one of the most important characteristics of glaciers which can cause serious natural disasters. For this reason, monitoring this massive blocks is a crucial task. Synthetic Aperture Radar (SAR) can operate all day in any weather conditions and the images acquired by SAR contain intensity and phase information, which are irreplaceable advantages in monitoring the surface movement of glaciers. Moreover, a variety of techniques like DInSAR and offset tracking, based on the information of SAR images, could be applied to measure the movement. Sangwang lake, a glacial lake in the Himalayas, has great potentially danger of outburst. Shie glacier is situated at the upstream of the Sangwang lake. Hence, it is significant to monitor Shie glacier surface movement to assess the risk of outburst. In this paper, 6 high resolution COSMO-SkyMed images spanning from August to December, 2016 are applied with offset tracking technique to estimate the surface movement of Shie glacier. The maximum velocity of Shie glacier surface movement is 51&thinsp;cm/d, which was observed at the end of glacier tongue, and the velocity is correlated with the change of elevation. Moreover, the glacier surface movement in summer is faster than in winter and the velocity decreases as the local temperature decreases. Based on the above conclusions, the glacier may break off at the end of tongue in the near future. The movement results extracted in this paper also illustrate the advantages of high resolution SAR images in monitoring the surface movement of small glaciers.

Download Full-text