A Multicomponent Temporal Coherence Model for 3-D Phase Unwrapping in Time-Series InSAR of Seasonal Deformation Areas
3-D phase unwrapping (PU) methods based on the 2-D linear temporal coherencemodel have been widely used in time-series interferometric synthetic aperture radar (TS-InSAR) for measuring topography and monitoring subtle deformation. However, the linear temporal coherencemodel can not characterize the...
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ftmdpi:oai:mdpi.com:/2072-4292/14/5/1080/ 2023-09-05T13:22:35+02:00 A Multicomponent Temporal Coherence Model for 3-D Phase Unwrapping in Time-Series InSAR of Seasonal Deformation Areas Bo Yang Huaping Xu Liming Jiang Ronggang Huang Zhiwei Zhou Hansheng Wang Wei Liu agris 2022-02-22 application/pdf https://doi.org/10.3390/rs14051080 EN eng Multidisciplinary Digital Publishing Institute Engineering Remote Sensing https://dx.doi.org/10.3390/rs14051080 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 14; Issue 5; Pages: 1080 interferometric synthetic aperture radar (InSAR) time-series InSAR (TS-InSAR) seasonal deformation multicomponent temporal coherence model 3-D phase unwrapping (3-D PU) Cramér–Rao bound (CRB) uncertainty evaluation Text 2022 ftmdpi https://doi.org/10.3390/rs14051080 2023-08-13T23:53:38Z 3-D phase unwrapping (PU) methods based on the 2-D linear temporal coherencemodel have been widely used in time-series interferometric synthetic aperture radar (TS-InSAR) for measuring topography and monitoring subtle deformation. However, the linear temporal coherencemodel can not characterize the coherence of highly coherent pixels accurately in seasonal deformation areas, where nonlinear deformation is deterministic and nonnegligible. Especially, for urban areas with groundwater or thermal dilation seasonal changes or permafrost regions, the nonlinear deformation is usually associated with periodic temperature changes. In this work, a general multi-component temporal coherence model, which considers multiple components including the seasonal deformation, is proposed for 3-D PU of seasonal deformation areas. Moreover, the uncertainty evaluation criterion, based on Cramér–Rao bound (CRB), is derived for TS-InSAR. The experimental results, obtained by applying the multi-component temporal coherence model to a data set acquired from January 2012 to February 2016 over the Beijing Capital International Airport area, confirm the effectiveness of the proposed method. High phase consistency, accurate corrected digital elevation model (DEM) and deformation information monitoring with high-density and high-coverage PS pixels are achieved. Under the same iterations and TS-InSAR procedure, the enhanced performance by the proposed model is illustrated by comparing with that of linear model in terms of phase consistency of 3-D phase unwrapping, PSCs selection at each step, and final results evaluation. In summary, the number of phase-consistency edges after 3-D PU is increased by about 15%, the number of final PS pixels selected with the same coherence threshold constraint is increased by about 10%, and more PS pixels provide a low uncertainty in residual topography, mean deformation velocity and seasonal amplitude estimation. Text permafrost MDPI Open Access Publishing Remote Sensing 14 5 1080 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
interferometric synthetic aperture radar (InSAR) time-series InSAR (TS-InSAR) seasonal deformation multicomponent temporal coherence model 3-D phase unwrapping (3-D PU) Cramér–Rao bound (CRB) uncertainty evaluation |
spellingShingle |
interferometric synthetic aperture radar (InSAR) time-series InSAR (TS-InSAR) seasonal deformation multicomponent temporal coherence model 3-D phase unwrapping (3-D PU) Cramér–Rao bound (CRB) uncertainty evaluation Bo Yang Huaping Xu Liming Jiang Ronggang Huang Zhiwei Zhou Hansheng Wang Wei Liu A Multicomponent Temporal Coherence Model for 3-D Phase Unwrapping in Time-Series InSAR of Seasonal Deformation Areas |
topic_facet |
interferometric synthetic aperture radar (InSAR) time-series InSAR (TS-InSAR) seasonal deformation multicomponent temporal coherence model 3-D phase unwrapping (3-D PU) Cramér–Rao bound (CRB) uncertainty evaluation |
description |
3-D phase unwrapping (PU) methods based on the 2-D linear temporal coherencemodel have been widely used in time-series interferometric synthetic aperture radar (TS-InSAR) for measuring topography and monitoring subtle deformation. However, the linear temporal coherencemodel can not characterize the coherence of highly coherent pixels accurately in seasonal deformation areas, where nonlinear deformation is deterministic and nonnegligible. Especially, for urban areas with groundwater or thermal dilation seasonal changes or permafrost regions, the nonlinear deformation is usually associated with periodic temperature changes. In this work, a general multi-component temporal coherence model, which considers multiple components including the seasonal deformation, is proposed for 3-D PU of seasonal deformation areas. Moreover, the uncertainty evaluation criterion, based on Cramér–Rao bound (CRB), is derived for TS-InSAR. The experimental results, obtained by applying the multi-component temporal coherence model to a data set acquired from January 2012 to February 2016 over the Beijing Capital International Airport area, confirm the effectiveness of the proposed method. High phase consistency, accurate corrected digital elevation model (DEM) and deformation information monitoring with high-density and high-coverage PS pixels are achieved. Under the same iterations and TS-InSAR procedure, the enhanced performance by the proposed model is illustrated by comparing with that of linear model in terms of phase consistency of 3-D phase unwrapping, PSCs selection at each step, and final results evaluation. In summary, the number of phase-consistency edges after 3-D PU is increased by about 15%, the number of final PS pixels selected with the same coherence threshold constraint is increased by about 10%, and more PS pixels provide a low uncertainty in residual topography, mean deformation velocity and seasonal amplitude estimation. |
format |
Text |
author |
Bo Yang Huaping Xu Liming Jiang Ronggang Huang Zhiwei Zhou Hansheng Wang Wei Liu |
author_facet |
Bo Yang Huaping Xu Liming Jiang Ronggang Huang Zhiwei Zhou Hansheng Wang Wei Liu |
author_sort |
Bo Yang |
title |
A Multicomponent Temporal Coherence Model for 3-D Phase Unwrapping in Time-Series InSAR of Seasonal Deformation Areas |
title_short |
A Multicomponent Temporal Coherence Model for 3-D Phase Unwrapping in Time-Series InSAR of Seasonal Deformation Areas |
title_full |
A Multicomponent Temporal Coherence Model for 3-D Phase Unwrapping in Time-Series InSAR of Seasonal Deformation Areas |
title_fullStr |
A Multicomponent Temporal Coherence Model for 3-D Phase Unwrapping in Time-Series InSAR of Seasonal Deformation Areas |
title_full_unstemmed |
A Multicomponent Temporal Coherence Model for 3-D Phase Unwrapping in Time-Series InSAR of Seasonal Deformation Areas |
title_sort |
multicomponent temporal coherence model for 3-d phase unwrapping in time-series insar of seasonal deformation areas |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2022 |
url |
https://doi.org/10.3390/rs14051080 |
op_coverage |
agris |
genre |
permafrost |
genre_facet |
permafrost |
op_source |
Remote Sensing; Volume 14; Issue 5; Pages: 1080 |
op_relation |
Engineering Remote Sensing https://dx.doi.org/10.3390/rs14051080 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs14051080 |
container_title |
Remote Sensing |
container_volume |
14 |
container_issue |
5 |
container_start_page |
1080 |
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1776203087157919744 |