Glacier motion estimation using SAR offset-tracking procedures

Two image-to-image patch offset techniques for estimating feature motion between satellite synthetic aperture radar (SAR) images are discussed. Intensity tracking, based on patch intensity cross-correlation optimization, and coherence tracking, based on patch coherence optimization, are used to estimate the movement of glacier surfaces between two SAR images in both slant-range and azimuth direction. The accuracy and application range of the two methods are examined in the case of the surge of Monacobreen in Northern Svalbard between 1992 and 1996. Offset-tracking procedures of SAR images are an alternative to differential SAR interferometry for the estimation of glacier motion when differential SAR interferometry is limited by loss of coherence, i.e., in the case of rapid and incoherent flow and of large acquisition time intervals between the two SAR images. In addition, an offset-tracking procedure in the azimuth direction may be combined with differential SAR interferometry in the slant-range direction in order to retrieve a two-dimensional displacement map when SAR data of only one orbit configuration are available

Seasonal glacier surface velocity fluctuation and contribution of the Eastern and Western Tributary Glaciers in Amery Ice Shelf, East Antarctica

Glaciers play a crucial role in the study of the climate change pattern of the Earth. Remote sensing with access to large archives of data has the ability to monitor glaciers frequently throughout the year. Therefore, remote sensing is the most beneficial tool for the study of glacier dynamics. Fed by many tributaries from different sides, the Amery Ice Shelf (AIS) is one of the largest ice shelves that drains ice from the Antarctic ice sheet into the Southern Ocean. This study focuses on the eastern and the western tributaries of the AIS. The primary objective of the study was to derive the velocity of the tributary glaciers and the secondary objective was to compare variations in their velocities between the summer and winter season. This study was carried on using the European Space Agency’s (ESA) Sentinel-1 satellite’s Synthetic Aperture Radar (SAR) data acquired from the Sentinel data portal. Offset tracking method was applied to the Ground Range Detected (GRD) product of the Sentinel-1 interferometric wide (IW) swath acquisition mode. The maximum velocity in summer was observed to be around 610 m/yr in the eastern tributary glacier meeting the ice shelf near the Pickering Nunatak, and around 345 m/yr in the Charybdis Glacier Basin from the western side. The maximum velocity in the winter was observed to be 553 m/yr in the eastern side near the Pickering Nunatak whereas 323 m/yr from the western side in the Charybdis Glacier Basin. The accuracy of the derived glacier velocities was computed using bias and root mean square (RMS) error. For the analysis, the publicly available velocity datasets were used. The accuracy based on RMS error was observed to be 85-90% for both seasons with bias values up to 25 m/yr and root mean square error values up to 30 m/yr

The glaciers climate change initiative: Methods for creating glacier area, elevation change and velocity products

Glaciers and their changes through time are increasingly obtained from a wide range of satellite sensors. Due to the often remote location of glaciers in inaccessible and high-mountain terrain, satellite observations frequently provide the only available measurements. Furthermore, satellite data provide observations of glacier character- istics that are difficult to monitor using ground-based measurements, thus complementing the latter. In the Glaciers_cci project of the European Space Agency (ESA), three of these characteristics are investigated in detail: glacier area, elevation change and surface velocity. We use (a) data from optical sensors to derive glacier outlines, (b) digital elevation models from at least two points in time, (c) repeat altimetry for determining elevation changes, and (d) data from repeat optical and microwave sensors for calculating surface velocity. For the latter, the two sensor types provide complementary information in terms of spatio-temporal coverage. While (c) and (d) can be generated mostly automatically, (a) and (b) require the intervention of an analyst. Largely based on the results of various round robin experiments (multi-analyst benchmark studies) for each of the products, we suggest and describe the most suitable algorithms for product creation and provide recommendations concerning their practical implementation and the required post-processing. For some of the products (area, velocity) post-processing can influence product quality more than the main-processing algorithm

Seasonal and interannual ice velocity changes of Polar Record Glacier, East Antarctica

We present a study of seasonal and interannual ice velocity changes at Polar Record Glacier, East Antarctica, using ERS-1/2, Envisat and PALSAR data with D-InSAR and intensity tracking. Ice flow showed seasonal variations at the front of the glacier tongue. Velocities in winter were 19% less than velocities during summer. No significant interannual changes were detected. Ice velocities in the grounding zone and grounded glacier did not show clear seasonal or interannual changes. The distributio of the seasonal variations suggests that the cause for the changes should be localized. Possible causes are seasonal sea-ice changes and iceberg blocking. Satellite images show that the sea ice surrounding Polar Record Glacier undergoes seasonal changes. Frozen sea ice in winter slowed the huge iceberg, and provided increased resistance to the glacier flow. The interaction between the glacier tongue, ice berg and sea ice significantly influences their flow pattern

Displacement Estimation by Maximum Likelihood Texture Tracking

International audienceThis paper presents a novel method to estimate displacement by maximum-likelihood (ML) texture tracking. The observed polarimetric synthetic aperture radar (PolSAR) data-set is composed by two terms: the scalar texture parameter and the speckle component. Based on the Spherically Invariant Random Vectors (SIRV) theory, the ML estimator of the texture is computed. A generalization of the ML texture tracking based on the Fisher probability density function (pdf) modeling is introduced. For random variables with Fisher distributions, the ratio distribution is established. The proposed method is tested with both simulated PolSAR data and spaceborne PolSAR images provided by the TerraSAR-X (TSX) and the RADARSAT-2 (RS-2) sensors

Estimation of glacier surface velocity of Drang- drung glacier by DInSAR technique using Sentinel- 1 SLC SAR data

Glaciers are sensitive to climate change, especially the mountain glaciers due to their relatively small size they show rapid and fast changes to the ongoing trend of warming in climate. In the Himalayan region, the glaciers serve as important source of water for agriculture, power supply and tourism related activities. Glacier velocity gives information about the glacier health and helps in understanding the climate change, mass balance, and glacier dynamics. Differential SAR Interferometry (DInSAR) is the radar interferometry technique for measuring surface changes with a higher accuracy up to millimeter range. Velocity estimates are important to understand the glacier related hazards and can help in alleviating the possible future damage downslope. In this study, the velocity of one of the biggest and benchmark glaciers in Zanskar region has been estimated using DInSAR technique on Sentinel 1 SLC data. The results show that glacier has moved approximately 1m over a period of 12 days

Autonomous Repeat Image Feature Tracking (autoRIFT) and Its Application for Tracking Ice Displacement

In this paper, we build on past efforts with regard to the implementation of an efficient feature tracking algorithm for the mass processing of satellite images. This generic open-source feature tracking routine can be applied to any type of imagery to measure sub-pixel displacements between images. The routine consists of a feature tracking module (autoRIFT) that enhances computational efficiency and a geocoding module (Geogrid) that mitigates problems found in existing geocoding algorithms. When applied to satellite imagery, autoRIFT can run on a grid in the native image coordinates (such as radar or map) and, when used in conjunction with the Geogrid module, on a user-defined grid in geographic Cartesian coordinates such as Universal Transverse Mercator or Polar Stereographic. To validate the efficiency and accuracy of this approach, we demonstrate its use for tracking ice motion by using ESA’s Sentinel-1A/B radar data (seven pairs) and NASA’s Landsat-8 optical data (seven pairs) collected over Greenland’s Jakobshavn Isbræ glacier in 2017. Feature-tracked velocity errors are characterized over stable surfaces, where the best Sentinel-1A/B pair with a 6 day separation has errors in X/Y of 12 m/year or 39 m/year, compared to 22 m/year or 31 m/year for Landsat-8 with a 16-day separation. Different error sources for radar and optical image pairs are investigated, where the seasonal variation and the error dependence on the temporal baseline are analyzed. Estimated velocities were compared with reference velocities derived from DLR’s TanDEM-X SAR/InSAR data over the fast-moving glacier outlet, where Sentinel-1 results agree within 4% compared to 3–7% for Landsat-8. A comprehensive apples-to-apples comparison is made with regard to runtime and accuracy between multiple implementations of the proposed routine and the widely-used “dense ampcor" program from NASA/JPL’s ISCE software. autoRIFT is shown to provide two orders of magnitude of runtime improvement with a 20% improvement in accuracy

Surface velocity and ice discharge of the ice cap on King George Island, Antarctica

Glaciers on King George Island, Antarctica, have shown retreat and surface lowering in recent decades, concurrent with increasing air temperatures. A large portion of the glacier perimeter is ocean-terminating, suggesting possible large mass losses due to calving and submarine melting. Here we estimate the ice discharge into the ocean for the King George Island ice cap. L-band synthetic aperture radar images covering the time-span January 2008 to January 2011 over King George Island are processed using an intensity-tracking algorithm to obtain surface velocity measurements. Pixel offsets from 40 pairs of radar images are analysed and inverted to estimate a weighted average surface velocity field. Ice thicknesses are derived from simple principles of ice flow mechanics using the computed surface velocity fields and in situ thickness data. The maximum ice surface speeds reach mayor que 225 m/yr, and the total ice discharge for the analysed flux gates of King George Island is estimated to be 0.720+/-0.428 Gt/yr, corresponding to a specific mass loss of 0.64+/-0.38 m w.e./yr over the area of the entire ice cap (1127 km2)