Three-Dimensional Ice-Flow Recovery from Ascending–Descending DInSAR Pairs and Surface-Parallel Flow Hypothesis: A Simplified Implementation in SNAP Software

By considering two differential interferometric SAR signals, recovered from synthetic aperture radar (SAR) images, it has been possible to estimate the glacier velocity vector, from a method proposed by the authors Joughin, Kwok, and Fahnestock (JKF) in 1998. Although the JKF method normally works w...

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Published in:Remote Sensing
Main Authors: Alejandro Téllez-Quiñones, Adán Salazar-Garibay, Beatriz I. Cruz-Sánchez, Hugo Carlos-Martínez, Juan C. Valdiviezo-Navarro, Victor Soto
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2025
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Online Access:https://doi.org/10.3390/rs17071168
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author Alejandro Téllez-Quiñones
Adán Salazar-Garibay
Beatriz I. Cruz-Sánchez
Hugo Carlos-Martínez
Juan C. Valdiviezo-Navarro
Victor Soto
author_facet Alejandro Téllez-Quiñones
Adán Salazar-Garibay
Beatriz I. Cruz-Sánchez
Hugo Carlos-Martínez
Juan C. Valdiviezo-Navarro
Victor Soto
author_sort Alejandro Téllez-Quiñones
collection MDPI Open Access Publishing
container_issue 7
container_start_page 1168
container_title Remote Sensing
container_volume 17
description By considering two differential interferometric SAR signals, recovered from synthetic aperture radar (SAR) images, it has been possible to estimate the glacier velocity vector, from a method proposed by the authors Joughin, Kwok, and Fahnestock (JKF) in 1998. Although the JKF method normally works well under certain SAR observation conditions, we found a reformulated version of the main equation of this technique that may improve this interesting methodology. Thus, we present a mathematical review of this method, and a validation of our result in terms of accuracy, with some computer simulations. The innovation proposed is a simplified way to implement JKF’s work in the Sentinel Application Platform (SNAP) software, exemplified with some images from the Canadian Arctic. Generally, a north–east–up displacement estimation is considered, by using reference orthogonal coordinates, independent of the SAR image coordinates. However, we propose a methodology to estimate this velocity vector in terms of ascending or descending image coordinates. Given the importance of the JKF work, we believe that this investigation could contribute to the improvement of this technique, beyond the existence of other modern and independent methodologies.
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spelling ftmdpi:oai:mdpi.com:/2072-4292/17/7/1168/ 2025-04-27T14:24:49+00:00 Three-Dimensional Ice-Flow Recovery from Ascending–Descending DInSAR Pairs and Surface-Parallel Flow Hypothesis: A Simplified Implementation in SNAP Software Alejandro Téllez-Quiñones Adán Salazar-Garibay Beatriz I. Cruz-Sánchez Hugo Carlos-Martínez Juan C. Valdiviezo-Navarro Victor Soto agris 2025-03-26 application/pdf https://doi.org/10.3390/rs17071168 eng eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs17071168 https://creativecommons.org/licenses/by/4.0/ Remote Sensing Volume 17 Issue 7 Pages: 1168 synthetic aperture radar image processing DInSAR applications Text 2025 ftmdpi https://doi.org/10.3390/rs17071168 2025-03-31T14:26:03Z By considering two differential interferometric SAR signals, recovered from synthetic aperture radar (SAR) images, it has been possible to estimate the glacier velocity vector, from a method proposed by the authors Joughin, Kwok, and Fahnestock (JKF) in 1998. Although the JKF method normally works well under certain SAR observation conditions, we found a reformulated version of the main equation of this technique that may improve this interesting methodology. Thus, we present a mathematical review of this method, and a validation of our result in terms of accuracy, with some computer simulations. The innovation proposed is a simplified way to implement JKF’s work in the Sentinel Application Platform (SNAP) software, exemplified with some images from the Canadian Arctic. Generally, a north–east–up displacement estimation is considered, by using reference orthogonal coordinates, independent of the SAR image coordinates. However, we propose a methodology to estimate this velocity vector in terms of ascending or descending image coordinates. Given the importance of the JKF work, we believe that this investigation could contribute to the improvement of this technique, beyond the existence of other modern and independent methodologies. Text Arctic MDPI Open Access Publishing Arctic The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) Remote Sensing 17 7 1168
spellingShingle synthetic aperture radar
image processing
DInSAR applications
Alejandro Téllez-Quiñones
Adán Salazar-Garibay
Beatriz I. Cruz-Sánchez
Hugo Carlos-Martínez
Juan C. Valdiviezo-Navarro
Victor Soto
Three-Dimensional Ice-Flow Recovery from Ascending–Descending DInSAR Pairs and Surface-Parallel Flow Hypothesis: A Simplified Implementation in SNAP Software
title Three-Dimensional Ice-Flow Recovery from Ascending–Descending DInSAR Pairs and Surface-Parallel Flow Hypothesis: A Simplified Implementation in SNAP Software
title_full Three-Dimensional Ice-Flow Recovery from Ascending–Descending DInSAR Pairs and Surface-Parallel Flow Hypothesis: A Simplified Implementation in SNAP Software
title_fullStr Three-Dimensional Ice-Flow Recovery from Ascending–Descending DInSAR Pairs and Surface-Parallel Flow Hypothesis: A Simplified Implementation in SNAP Software
title_full_unstemmed Three-Dimensional Ice-Flow Recovery from Ascending–Descending DInSAR Pairs and Surface-Parallel Flow Hypothesis: A Simplified Implementation in SNAP Software
title_short Three-Dimensional Ice-Flow Recovery from Ascending–Descending DInSAR Pairs and Surface-Parallel Flow Hypothesis: A Simplified Implementation in SNAP Software
title_sort three-dimensional ice-flow recovery from ascending–descending dinsar pairs and surface-parallel flow hypothesis: a simplified implementation in snap software
topic synthetic aperture radar
image processing
DInSAR applications
topic_facet synthetic aperture radar
image processing
DInSAR applications
url https://doi.org/10.3390/rs17071168