Glacier Monitoring Using Frequency Domain Offset Tracking Applied to Sentinel-1 Images: A Product Performance Comparison

Amitrano, Donato; Guida, Raffaella; Martino, Gerardo Di; Iodice, Antonio

doi:10.3390/rs11111322

Cited by 13 publications

(6 citation statements)

References 58 publications

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“…This technology was first introduced into the field of optical data [27] and was later widely used in applications based on SAR images [18]. Among the related algorithms, normalized cross-correlation (NCC) [28] and its variants calculated in the frequency domain [29,30] are the most popular methods to find the corresponding template. However, if there is no distinct pattern or texture on the surface of the glacier to obtain reliable correlation, the matching result may be greatly damaged.…”

Section: Offset Tracking-based Methodsmentioning

confidence: 99%

Glacier Surface Motion Estimation from SAR Intensity Images Based on Subpixel Gradient Correlation

et al. 2020

Sensors

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With the current extensive availability of synthetic-aperture radar (SAR) datasets with high temporal (e.g., a repeat cycle of a few or a dozen days) and spatial resolution (e.g., in the order of ∼1 m), radar remote sensing possesses an increasing potential for the monitoring of glacier surface motion thanks to the nearly weather and time-independent advantages. This paper proposes a robust subpixel frequency-based image correlation method for dense matching and integrates the improved matching into a workflow of glacier surface motion estimation using SAR intensity images with specific pre-processing and post-processing steps. The proposed matching method combines complex edge maps and local upsampling in the frequency domain for subpixel intensity tracking, which ensure the accuracy and robustness of glacier surface motion estimation. Experiments were carried out with TerraSAR-X and Sentinel-1 images covering two glacier areas in pole and alpine regions. The results of the monitoring and investigation of glacier motion validate the feasibility and reliability of the presented motion estimation method based on subpixel gradient correlation. The comparative results using both simulated and real SAR data indicate that the proposed matching method outperforms commonly used correlation-based matching methods in terms of matching accuracy and the ability to obtain correct matches.

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Section: Offset Tracking-based Methodsmentioning

confidence: 99%

Glacier Surface Motion Estimation from SAR Intensity Images Based on Subpixel Gradient Correlation

et al. 2020

Sensors

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“…As per various authors this method is ideal for estimation of glacier velocity across the glaciers of the world. [6][7][8] . A 128-pixel window is chosen to track the offset in a master and slave image.…”

Section: 𝑖 = 𝐷𝑁 𝐴mentioning

confidence: 99%

Line-of-Sight Glacier Velocity Estimation of Transboundary Glaciers in the Eastern Himalayas Using High-Resolution TerraSAR-X Data

et al. 2023

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Glacier velocity is one of the critical parameters for understanding the current health status of a glacier. According to the momentum law, mass is inversely proportional to velocity. Higher velocity may indicate lesser mass. Fifteen transboundary glaciers from the eastern Himalayas in the vicinity of India, Nepal, Bhutan, and China are chosen for the estimation of glacier velocity. These glaciers are Changshang, Rathong, South Lhonak, South Simvo, Talung, Tongshiong, Yalung, Zemu, Glacier 2, Glacier 3, Kaer, Ktr Gr 193, Middle Lhonak, North Lhonak, and Ktr Gr 171 (Lhonak Nepal) covering total area of 440.92 km 2 . A remote sensing and GIS-based approach is considered for the study. High-resolution Synthetic Aperture Radar data of TerraSAR-X was acquired from the German Aerospace Center (DLR) by European Space Agency for study area in the year 2020-2021. Satellite data are preprocessed using radiometric calibration and multi-look for speckle noise reduction. These datasets are co-registered using SRTM Digital Elevation Model. Offset Tracking is applied to estimate the glacier velocity. The maximum velocity in all glaciers ranged from 14.31-84.26ma -1 . The average velocity ranged from 1.78-7.09ma −1 . The glacier having highest average velocity is South Lhonak glacier. This glacier is melting rapidly in the last few decades. Near the snout of this glacier lies a glacial lake made up of a moraine dam. For quality assessment, latest field-based results of 2018 and observed results of 2021 were compared. It has been noticed that there is a variation of approximately 10%.

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“…To measure the CRs displacement in image pairs, the so-called "phase correlation" method was used, which is a Fourier-based matching technique considered to be more accurate and robust than other correlation-based methods (Amitrano et al, 2019). Two PAZ descending images in which the HG CR was visible were utilized for the analysis.…”

Section: Sar Based Displacement Estimationmentioning

confidence: 99%

Monitoring Hanging Glacier Dynamics From Sar Images Using Corner Reflectors and Field Measurements in the Mont-Blanc Massif

Kaushik

Leinß²,

Ravanel³

et al. 2022

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. This paper focuses on the monitoring of a small hanging glacier with Synthetic Aperture Radar (SAR) images using a combination of artificial Corner Reflectors (CRs) and dGNSS field measurements. First, to test the performance of the CRs in high-resolution X-band and medium-resolution C-band images acquired by PAZ and Sentinel-1 satellites respectively, a series of tests was performed with two CRs installed in the Chamonix valley. After the confirmation of good visibility in the valley datasets from both satellites, four CRs were installed in summer 2021 on a steep (&approx; 52° average slope) hanging glacier on the North face of Aiguille du Midi (3842 ma.s.l., Mont-Blanc massif). After the successful installation on the hanging glacier, all CRs were visible in both sets of images (PAZ and Sentinel-1). Using the CRs as a reference, glacier displacements were estimated in SAR images using complex cross-correlation, and validated by using ground measurements (dGNSS) and theoretical relationships between ice thickness and surface velocity. We observed average summer velocities of &approx; 0.05 m/day at the front of the glacier from field measurements and &approx; 0.04 m/day from SAR displacement estimates. The study shows the potential and limitations of using CRs as a tool for monitoring glaciers in complex topographies.

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Glacier Monitoring Using Frequency Domain Offset Tracking Applied to Sentinel-1 Images: A Product Performance Comparison

Cited by 13 publications

References 58 publications

Glacier Surface Motion Estimation from SAR Intensity Images Based on Subpixel Gradient Correlation

Glacier Surface Motion Estimation from SAR Intensity Images Based on Subpixel Gradient Correlation

Line-of-Sight Glacier Velocity Estimation of Transboundary Glaciers in the Eastern Himalayas Using High-Resolution TerraSAR-X Data

Monitoring Hanging Glacier Dynamics From Sar Images Using Corner Reflectors and Field Measurements in the Mont-Blanc Massif

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