3D Surface velocity retrieval of mountain glacier using an offset tracking technique applied to ascending and descending SAR constellation data: a case study of the Yiga Glacier

2018 ◽  
Vol 12 (6) ◽  
pp. 614-624
Author(s):  
Qun Wang ◽  
Jinghui Fan ◽  
Wei Zhou ◽  
Liqiang Tong ◽  
Zhaocheng Guo ◽  
...  
Keyword(s):  
Surface Velocity ◽  
Mountain Glacier ◽  
Tracking Technique ◽  
3D Surface ◽  
Offset Tracking

scholarly journals Retrieving and Verifying Three-Dimensional Surface Motion Displacement of Mountain Glacier from Sentinel-1 Imagery Using Optimized Method

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1793
Author(s):  
Yanqiang Wang ◽  
Jun Zhao ◽  
Zhongqin Li ◽  
Mingjun Zhang ◽  
Yuchun Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Three Dimensional ◽  
Measurement Data ◽  
Surface Velocity ◽  
Special Importance ◽  
Mountain Glacier ◽  
Surface Motion ◽  
Mountain Glaciers ◽  
3D Surface ◽  
Offset Tracking

The time series study of glacier movement is of special importance for rational management of freshwater resources, studying glacier evolution, understanding mechanism of glacier movement, and assessing disasters caused by glacier movement. In this paper, we put forward an optimization scheme for the shortcomings in the calculation method of using remote sensing to invert the three-dimensional (3D) surface motion displacement of glacier. The optimized method consists of Offset Tracking method, Optimizing the offset tracking results by means of iterative filtering, OT-SBAS technology and Conversion of 3D surface motion displacement of glacier. The Urumqi Glacier No. 1 was selected to test the optimized method. The 3D surface motion displacement of Urumqi Glacier No. 1 was retrieved by using the optimized method based on the ascending and descending Sentinel-1 datasets from 19 April to 29 August 2018. The distribution of 3D surface velocity of the Urumqi Glacier No. 1 was obtained in time series, and the accuracy of the inversion results was evaluated by using the field measurement data. The results show that the accuracies of the inverted displacements of east branch of Urumqi Glacier No. 1 (UG1E) were about 0.062, 0.063, and 0.152 m in the east, north and vertical directions, and these values for the west branch (UG1W) were 0.015, 0.020 and 0.026 m, respectively. It is indicated that using Sentinel-1 ascending and descending data and using the optimized method to retrieve the 3D surface motion displacement of glacier should satisfy the requirements of inversing the 3D surface motion displacement of high-latitude mountain glaciers in China.

scholarly journals Monitoring and Analyzing Mountain Glacier Surface Movement Using SAR Data and a Terrestrial Laser Scanner: A Case Study of the Himalayas North Slope Glacier Area

2019 ◽  
Vol 11 (6) ◽  
pp. 625 ◽  
Author(s):  
Jinghui Fan ◽  
Qun Wang ◽  
Guang Liu ◽  
Lu Zhang ◽  
Zhaocheng Guo ◽  
...  
Keyword(s):  
Laser Scanner ◽  
Maximum Velocity ◽  
Point Clouds ◽  
Time Interval ◽  
Terrestrial Laser Scanner ◽  
Mountain Glacier ◽  
Surface Movement ◽  
Tracking Technique ◽  
Sar Data ◽  
Offset Tracking

The offset tracking technique based on synthetic aperture radar (SAR) image intensity information can estimate glacier displacement even when glacier velocities are high and the time interval between images is long, allowing for the broad use of this technique in glacier velocity monitoring. Terrestrial laser scanners, a non-contact measuring system, can measure the velocity of a glacier even if there are no control points arranged on a glacier. In this study, six COSMO-SkyMed images acquired between 31 July and 22 December 2016 were used to obtain the glacial movements of five glaciers on the northern slope of the central Himalayas using the offset tracking approach. During the period of image acquirement, a terrestrial laser scanner was used, and point clouds of two periods in a small area at the terminus of the Pingcuoliesa Glacier were obtained. By selecting three fixed areas of the point clouds that have similar shapes across two periods, the displacements of the centers of gravity of the selected areas were calculated by using contrast analyses of feature points. Although the overall low-density point clouds data indicate that the glacial surfaces have low albedos relative to the wavelength of the terrestrial laser scanner and the effect of its application is therefore influenced in this research, the registration accuracy of 0.0023 m/d in the non-glacial areas of the scanner’s measurements is acceptable, considering the magnitude of 0.072 m/d of the minimum glacial velocity measured by the scanner. The displacements from the point clouds broadly agree with the results of the offset tracking technique in the same area, which provides further evidence of the reliability of the measurements of the SAR data in addition to the analyses of the root mean squared error of the velocity residuals in non-glacial areas. The analysis of the movement of five glaciers in the study area revealed the dynamic behavior of these glacial surfaces across five periods. G089972E28213N Glacier, Pingcuoliesa Glacier and Shimo Glacier show increasing surface movement velocities from the terminus end to the upper part with elevations of 1500 m, 4500 m, and 6400 m, respectively. The maximum velocities on the glacial surface profiles were 31.69 cm/d, 62.40 cm/d, and 42.00 cm/d, respectively. In contrast, the maximum velocity of Shie Glacier, 50.60 cm/d, was observed at the glacier’s terminus. For each period, Glacier G090138E28210N exhibited similar velocity values across the surface profile, with a maximum velocity of 39.70 cm/d. The maximum velocities of G089972E28213N Glacier, Pingcuoliesa Glacier, and Shie Glacier occur in the areas where the topography is steepest. In general, glacial surface velocities are higher in the summer than in the winter in this region. With the assistance of a terrestrial laser scanner with optimized wavelengths or other proper ground-based remote sensing instruments, the offset tracking technique based on high-resolution satellite SAR data should provide more reliable and detailed information for local and even single glacial surface displacement monitoring.

scholarly journals Monitoring Lakes Surface Water Velocity with SAR: A Feasibility Study on Lake Garda, Italy

2021 ◽  
Vol 13 (12) ◽  
pp. 2293
Author(s):  
Marina Amadori ◽  
Virginia Zamparelli ◽  
Giacomo De Carolis ◽  
Gianfranco Fornaro ◽  
Marco Toffolon ◽  
...  
Keyword(s):  
Surface Water ◽  
Wind Waves ◽  
Test Site ◽  
Water Velocity ◽  
Surface Velocity ◽  
Medium Size ◽  
Small Scale ◽  
Lake Garda ◽  
Marine Applications

The SAR Doppler frequencies are directly related to the motion of the scatterers in the illuminated area and have already been used in marine applications to monitor moving water surfaces. Here we investigate the possibility of retrieving surface water velocity from SAR Doppler analysis in medium-size lakes. ENVISAT images of the test site (Lake Garda) are processed and the Doppler Centroid Anomaly technique is adopted. The resulting surface velocity maps are compared with the outputs of a hydrodynamic model specifically validated for the case study. Thermal images from MODIS Terra are used in support of the modeling results. The surface velocity retrieved from SAR is found to overestimate the numerical results and the existence of a bias is investigated. In marine applications, such bias is traditionally removed through Geophysical Model Functions (GMFs) by ascribing it to a fully developed wind waves spectrum. We found that such an assumption is not supported in our case study, due to the small-scale variations of topography and wind. The role of wind intensity and duration on the results from SAR is evaluated, and the inclusion of lake bathymetry and the SAR backscatter gradient is recommended for the future development of GMFs suitable for lake environments.

On the characterisation of open-flow seeding conditions for image-velocimetry techniques using UASs

2020 ◽  
Author(s):  
Silvano Fortunato Dal Sasso ◽  
Alonso Pizarro ◽  
Salvatore Manfreda
Keyword(s):  
River Discharge ◽  
Velocity Fields ◽  
Velocity Estimation ◽  
Surface Velocity ◽  
Seeding Density ◽  
Acquisition Time ◽  
Flow Conditions ◽  
Open Flow ◽  
Image Velocimetry

<p>In the last years, new technologies have been developed to monitor rivers in a real-time framework opening new opportunities and challenges for the research community and practitioners. Acquiring data in open flow conditions can be performed through the use of Unmanned Aerial System (UAS) to derive surface velocity fields and in consequence, river discharge. Significant work has been done to investigate the reliability of image-velocimetry techniques using numerical simulations and laboratory flume experiments, but, to date, the effects of environmental factors on velocity estimates are not addressed adequately. In this context, a critical variable is represented by the number of particles transiting on the water surface (defined as seeding density) during field surveys and their challenging dynamics along the cross-section, on both time and space. Seeding density has a significant effect on surface velocity estimation and river discharge accuracy. The goal of this study was, therefore, to evaluate the accuracy and feasibility of LSPIV and PTV techniques under different seeding and flow conditions using several footages acquired employing UASs. To this purpose, the seeding behaviour during the whole acquisition time was examined for each case study focusing on the quantification of essential variables such as seeding density, average tracers’ dimension, coefficient of variation of tracers’ area, and spatial dispersion of them in the field of view. For each case study, both image-velocimetry techniques have been applied considering several different sets of images to locally measure the accuracy of velocity estimations in challenging seeding conditions. Results show that the local seeding density, tracers’ dimension and their spatial distribution can strongly influence the reconstruction of velocity fields in natural stream reaches. Therefore, prior knowledge of seeding characteristics in the field can deal with the choice of the optimal image-velocimetry technique to use and the related setting parameters.</p>

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