Remote Sensing / Inferring 2D Local Surface-Deformation Velocities Based on PSI Analysis of Sentinel-1 Data : a Case Study of Öræfajökull, Iceland

Two-dimensional deformation estimates derived from Persistent Scatterer Interferometric (PSI) analysis of Synthetic Aperture Radar (SAR) data can improve the characterisation of spatially and temporally varying deformation processes of Earth’s surface. In this study, we examine the applicability of...

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Published in:Remote Sensing
Main Authors: Dittrich, Jirathana, Hölbling, Daniel, Tiede, Dirk, Saemundsson, Thorsteinn
Format: Article in Journal/Newspaper
Language:English
Published: MDPI 2022
Subjects:
Psi
Online Access:https://doi.org/10.3390/rs14133166
https://eplus.uni-salzburg.at/doi/10.3390/rs14133166
https://resolver.obvsg.at/urn:nbn:at:at-ubs:3-26219
id ftunivsalzburg:oai:eplus.uni-salzburg.at:7870432
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spelling ftunivsalzburg:oai:eplus.uni-salzburg.at:7870432 2023-05-15T16:48:19+02:00 Remote Sensing / Inferring 2D Local Surface-Deformation Velocities Based on PSI Analysis of Sentinel-1 Data : a Case Study of Öræfajökull, Iceland Dittrich, Jirathana Hölbling, Daniel Tiede, Dirk Saemundsson, Thorsteinn 38.03 38.99 PLUS:IFFB:ZGIS 2022 text/html https://doi.org/10.3390/rs14133166 https://eplus.uni-salzburg.at/doi/10.3390/rs14133166 https://resolver.obvsg.at/urn:nbn:at:at-ubs:3-26219 eng eng MDPI vignette : https://eplus.uni-salzburg.at/titlepage/urn/urn:nbn:at:at-ubs:3-26219/128 vignette : https://eplus.uni-salzburg.at/titlepage/doi/10.3390/rs14133166/128 doi:10.3390/rs14133166 https://eplus.uni-salzburg.at/doi/10.3390/rs14133166 urn:nbn:at:at-ubs:3-26219 https://resolver.obvsg.at/urn:nbn:at:at-ubs:3-26219 local:99146869044803331 system:AC16571038 cc-by_4 Persistent Scatterer Interferometry (PSI) Sentinel-1 local deformation 2D velocity slope deformation ellipsoid incidence angle projected local incidence angle Iceland Text Article 2022 ftunivsalzburg https://doi.org/10.3390/rs14133166 2023-04-09T05:05:25Z Two-dimensional deformation estimates derived from Persistent Scatterer Interferometric (PSI) analysis of Synthetic Aperture Radar (SAR) data can improve the characterisation of spatially and temporally varying deformation processes of Earth’s surface. In this study, we examine the applicability of Persistent Scatterer (PS) Line-Of-Sight (LOS) estimates in providing two-dimensional deformation information, focusing on the retrieval of the local surface-movement processes. Two Sentinel-1 image stacks, ascending and descending, acquired from 2015 to 2018, were analysed based on a single master interferometric approach. First, Interferometric SAR (InSAR) deformation signals were corrected for divergent plate spreading and the Glacial Isostatic Adjustment (GIA) signals. To constrain errors due to rasterisation and interpolation of the pointwise deformation estimates, we applied a vector-based decomposition approach to solve the system of linear equations, resulting in 2D vertical and horizontal surface-deformation velocities at the PSs. We propose, herein, a two-step decomposition procedure that incorporates the Projected Local Incidence Angle (PLIA) to solve for the potential slope-deformation velocity. Our derived 2D velocities reveal spatially detailed movement patterns of the active Svínafellsjökull slope, which agree well with the independent GPS time-series measurements available for this area. Jirathana Dittrich, Daniel Hölbling, Dirk Tiede and Þorsteinn Sæmundsson FWF-P29461-N29 Article in Journal/Newspaper Iceland ePLUS - Open Access Publikationsserver der Universität Salzburg Psi ENVELOPE(-63.000,-63.000,-64.300,-64.300) Svínafellsjökull ENVELOPE(-16.823,-16.823,64.021,64.021) Remote Sensing 14 13 3166
institution Open Polar
collection ePLUS - Open Access Publikationsserver der Universität Salzburg
op_collection_id ftunivsalzburg
language English
topic Persistent Scatterer Interferometry (PSI)
Sentinel-1
local deformation
2D velocity
slope deformation
ellipsoid incidence angle
projected local incidence angle
Iceland
spellingShingle Persistent Scatterer Interferometry (PSI)
Sentinel-1
local deformation
2D velocity
slope deformation
ellipsoid incidence angle
projected local incidence angle
Iceland
Dittrich, Jirathana
Hölbling, Daniel
Tiede, Dirk
Saemundsson, Thorsteinn
Remote Sensing / Inferring 2D Local Surface-Deformation Velocities Based on PSI Analysis of Sentinel-1 Data : a Case Study of Öræfajökull, Iceland
topic_facet Persistent Scatterer Interferometry (PSI)
Sentinel-1
local deformation
2D velocity
slope deformation
ellipsoid incidence angle
projected local incidence angle
Iceland
description Two-dimensional deformation estimates derived from Persistent Scatterer Interferometric (PSI) analysis of Synthetic Aperture Radar (SAR) data can improve the characterisation of spatially and temporally varying deformation processes of Earth’s surface. In this study, we examine the applicability of Persistent Scatterer (PS) Line-Of-Sight (LOS) estimates in providing two-dimensional deformation information, focusing on the retrieval of the local surface-movement processes. Two Sentinel-1 image stacks, ascending and descending, acquired from 2015 to 2018, were analysed based on a single master interferometric approach. First, Interferometric SAR (InSAR) deformation signals were corrected for divergent plate spreading and the Glacial Isostatic Adjustment (GIA) signals. To constrain errors due to rasterisation and interpolation of the pointwise deformation estimates, we applied a vector-based decomposition approach to solve the system of linear equations, resulting in 2D vertical and horizontal surface-deformation velocities at the PSs. We propose, herein, a two-step decomposition procedure that incorporates the Projected Local Incidence Angle (PLIA) to solve for the potential slope-deformation velocity. Our derived 2D velocities reveal spatially detailed movement patterns of the active Svínafellsjökull slope, which agree well with the independent GPS time-series measurements available for this area. Jirathana Dittrich, Daniel Hölbling, Dirk Tiede and Þorsteinn Sæmundsson FWF-P29461-N29
format Article in Journal/Newspaper
author Dittrich, Jirathana
Hölbling, Daniel
Tiede, Dirk
Saemundsson, Thorsteinn
author_facet Dittrich, Jirathana
Hölbling, Daniel
Tiede, Dirk
Saemundsson, Thorsteinn
author_sort Dittrich, Jirathana
title Remote Sensing / Inferring 2D Local Surface-Deformation Velocities Based on PSI Analysis of Sentinel-1 Data : a Case Study of Öræfajökull, Iceland
title_short Remote Sensing / Inferring 2D Local Surface-Deformation Velocities Based on PSI Analysis of Sentinel-1 Data : a Case Study of Öræfajökull, Iceland
title_full Remote Sensing / Inferring 2D Local Surface-Deformation Velocities Based on PSI Analysis of Sentinel-1 Data : a Case Study of Öræfajökull, Iceland
title_fullStr Remote Sensing / Inferring 2D Local Surface-Deformation Velocities Based on PSI Analysis of Sentinel-1 Data : a Case Study of Öræfajökull, Iceland
title_full_unstemmed Remote Sensing / Inferring 2D Local Surface-Deformation Velocities Based on PSI Analysis of Sentinel-1 Data : a Case Study of Öræfajökull, Iceland
title_sort remote sensing / inferring 2d local surface-deformation velocities based on psi analysis of sentinel-1 data : a case study of öræfajökull, iceland
publisher MDPI
publishDate 2022
url https://doi.org/10.3390/rs14133166
https://eplus.uni-salzburg.at/doi/10.3390/rs14133166
https://resolver.obvsg.at/urn:nbn:at:at-ubs:3-26219
op_coverage 38.03
38.99
PLUS:IFFB:ZGIS
long_lat ENVELOPE(-63.000,-63.000,-64.300,-64.300)
ENVELOPE(-16.823,-16.823,64.021,64.021)
geographic Psi
Svínafellsjökull
geographic_facet Psi
Svínafellsjökull
genre Iceland
genre_facet Iceland
op_relation vignette : https://eplus.uni-salzburg.at/titlepage/urn/urn:nbn:at:at-ubs:3-26219/128
vignette : https://eplus.uni-salzburg.at/titlepage/doi/10.3390/rs14133166/128
doi:10.3390/rs14133166
https://eplus.uni-salzburg.at/doi/10.3390/rs14133166
urn:nbn:at:at-ubs:3-26219
https://resolver.obvsg.at/urn:nbn:at:at-ubs:3-26219
local:99146869044803331
system:AC16571038
op_rights cc-by_4
op_doi https://doi.org/10.3390/rs14133166
container_title Remote Sensing
container_volume 14
container_issue 13
container_start_page 3166
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