A multiscale approach to estimating topographically correlated propagation delays in radar interferograms

Musé, Pablo - Hetland, Eric - Simons, Mark - Lin, Yunung Nina - DiCaprio, Christopher

Resumen:

When targeting small amplitude surface deformation, using repeat orbit Interferometric Synthetic Aperture Radar (InSAR) observations can be plagued by propagation delays, some of which correlate with topographic variations. These topographically‐correlated delays result from temporal variations in vertical stratification of the troposphere. An approximate model assuming a linear relationship between topography and interferometric phase has been used to correct observations with success in a few studies. Here, we present a robust approach to estimating the transfer function, K, between topography and phase that is relatively insensitive to confounding processes (earthquake deformation, phase ramps from orbital errors, tidal loading, etc.). Our approach takes advantage of a multiscale perspective by using a band‐pass decomposition of both topography and observed phase. This decomposition into several spatial scales allows us to determine the bands wherein correlation between topography and phase is significant and stable. When possible, our approach also takes advantage of any inherent redundancy provided by multiple interferograms constructed with common scenes. We define a unique set of component time intervals for a given suite of interferometric pairs. We estimate an internally consistent transfer function for each component time interval, which can then be recombined to correct any arbitrary interferometric pair. We demonstrate our approach on a synthetic example and on data from two locations: Long Valley Caldera, California, which experienced prolonged periods of surface deformation from pressurization of a deep magma chamber, and one coseismic interferogram from the 2007 Mw 7.8 Tocapilla earthquake in northern Chile. In both examples, the corrected interferograms show improvements in regions of high relief, independent of whether or not we pre‐correct the data for a source model. We believe that most of the remaining signals are predominately due to heterogeneous water vapor distribution that requires more sophisticated correction methods than those described here.


Detalles Bibliográficos
2010
Atmospheric delay
Multiscale analysis
InSAR
Long Valley Caldera
Tocopilla earthquake
Inglés
Universidad de la República
COLIBRI
https://hdl.handle.net/20.500.12008/38722
Acceso abierto
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
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author Musé, Pablo
author2 Hetland, Eric
Simons, Mark
Lin, Yunung Nina
DiCaprio, Christopher
author2_role author
author
author
author
author_facet Musé, Pablo
Hetland, Eric
Simons, Mark
Lin, Yunung Nina
DiCaprio, Christopher
author_role author
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collection COLIBRI
dc.creator.none.fl_str_mv Musé, Pablo
Hetland, Eric
Simons, Mark
Lin, Yunung Nina
DiCaprio, Christopher
dc.date.accessioned.none.fl_str_mv 2023-08-01T20:33:29Z
dc.date.available.none.fl_str_mv 2023-08-01T20:33:29Z
dc.date.issued.es.fl_str_mv 2010
dc.date.submitted.es.fl_str_mv 20230801
dc.description.abstract.none.fl_txt_mv When targeting small amplitude surface deformation, using repeat orbit Interferometric Synthetic Aperture Radar (InSAR) observations can be plagued by propagation delays, some of which correlate with topographic variations. These topographically‐correlated delays result from temporal variations in vertical stratification of the troposphere. An approximate model assuming a linear relationship between topography and interferometric phase has been used to correct observations with success in a few studies. Here, we present a robust approach to estimating the transfer function, K, between topography and phase that is relatively insensitive to confounding processes (earthquake deformation, phase ramps from orbital errors, tidal loading, etc.). Our approach takes advantage of a multiscale perspective by using a band‐pass decomposition of both topography and observed phase. This decomposition into several spatial scales allows us to determine the bands wherein correlation between topography and phase is significant and stable. When possible, our approach also takes advantage of any inherent redundancy provided by multiple interferograms constructed with common scenes. We define a unique set of component time intervals for a given suite of interferometric pairs. We estimate an internally consistent transfer function for each component time interval, which can then be recombined to correct any arbitrary interferometric pair. We demonstrate our approach on a synthetic example and on data from two locations: Long Valley Caldera, California, which experienced prolonged periods of surface deformation from pressurization of a deep magma chamber, and one coseismic interferogram from the 2007 Mw 7.8 Tocapilla earthquake in northern Chile. In both examples, the corrected interferograms show improvements in regions of high relief, independent of whether or not we pre‐correct the data for a source model. We believe that most of the remaining signals are predominately due to heterogeneous water vapor distribution that requires more sophisticated correction methods than those described here.
dc.identifier.citation.es.fl_str_mv Musé, P, Hetland, E, Simons, M, Lin, Y, DiCaprio, C. “A multiscale approach to estimating topographically correlated propagation delays in radar interferograms” [Preprint] Publicado en Geochemistry, Geophysics, Geosystems, 2010, v.11, no. 9. doi:10.1029/2010GC003228
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12008/38722
dc.language.iso.none.fl_str_mv en
eng
dc.rights.license.none.fl_str_mv Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:COLIBRI
instname:Universidad de la República
instacron:Universidad de la República
dc.subject.es.fl_str_mv Atmospheric delay
Multiscale analysis
InSAR
Long Valley Caldera
Tocopilla earthquake
dc.title.none.fl_str_mv A multiscale approach to estimating topographically correlated propagation delays in radar interferograms
dc.type.es.fl_str_mv Preprint
dc.type.none.fl_str_mv info:eu-repo/semantics/preprint
dc.type.version.none.fl_str_mv info:eu-repo/semantics/submittedVersion
description When targeting small amplitude surface deformation, using repeat orbit Interferometric Synthetic Aperture Radar (InSAR) observations can be plagued by propagation delays, some of which correlate with topographic variations. These topographically‐correlated delays result from temporal variations in vertical stratification of the troposphere. An approximate model assuming a linear relationship between topography and interferometric phase has been used to correct observations with success in a few studies. Here, we present a robust approach to estimating the transfer function, K, between topography and phase that is relatively insensitive to confounding processes (earthquake deformation, phase ramps from orbital errors, tidal loading, etc.). Our approach takes advantage of a multiscale perspective by using a band‐pass decomposition of both topography and observed phase. This decomposition into several spatial scales allows us to determine the bands wherein correlation between topography and phase is significant and stable. When possible, our approach also takes advantage of any inherent redundancy provided by multiple interferograms constructed with common scenes. We define a unique set of component time intervals for a given suite of interferometric pairs. We estimate an internally consistent transfer function for each component time interval, which can then be recombined to correct any arbitrary interferometric pair. We demonstrate our approach on a synthetic example and on data from two locations: Long Valley Caldera, California, which experienced prolonged periods of surface deformation from pressurization of a deep magma chamber, and one coseismic interferogram from the 2007 Mw 7.8 Tocapilla earthquake in northern Chile. In both examples, the corrected interferograms show improvements in regions of high relief, independent of whether or not we pre‐correct the data for a source model. We believe that most of the remaining signals are predominately due to heterogeneous water vapor distribution that requires more sophisticated correction methods than those described here.
eu_rights_str_mv openAccess
format preprint
id COLIBRI_23d1e8681ead2a855a7b66ef39529f8f
identifier_str_mv Musé, P, Hetland, E, Simons, M, Lin, Y, DiCaprio, C. “A multiscale approach to estimating topographically correlated propagation delays in radar interferograms” [Preprint] Publicado en Geochemistry, Geophysics, Geosystems, 2010, v.11, no. 9. doi:10.1029/2010GC003228
instacron_str Universidad de la República
institution Universidad de la República
instname_str Universidad de la República
language eng
language_invalid_str_mv en
network_acronym_str COLIBRI
network_name_str COLIBRI
oai_identifier_str oai:colibri.udelar.edu.uy:20.500.12008/38722
publishDate 2010
reponame_str COLIBRI
repository.mail.fl_str_mv mabel.seroubian@seciu.edu.uy
repository.name.fl_str_mv COLIBRI - Universidad de la República
repository_id_str 4771
rights_invalid_str_mv Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
spelling 2023-08-01T20:33:29Z2023-08-01T20:33:29Z201020230801Musé, P, Hetland, E, Simons, M, Lin, Y, DiCaprio, C. “A multiscale approach to estimating topographically correlated propagation delays in radar interferograms” [Preprint] Publicado en Geochemistry, Geophysics, Geosystems, 2010, v.11, no. 9. doi:10.1029/2010GC003228https://hdl.handle.net/20.500.12008/38722When targeting small amplitude surface deformation, using repeat orbit Interferometric Synthetic Aperture Radar (InSAR) observations can be plagued by propagation delays, some of which correlate with topographic variations. These topographically‐correlated delays result from temporal variations in vertical stratification of the troposphere. An approximate model assuming a linear relationship between topography and interferometric phase has been used to correct observations with success in a few studies. Here, we present a robust approach to estimating the transfer function, K, between topography and phase that is relatively insensitive to confounding processes (earthquake deformation, phase ramps from orbital errors, tidal loading, etc.). Our approach takes advantage of a multiscale perspective by using a band‐pass decomposition of both topography and observed phase. This decomposition into several spatial scales allows us to determine the bands wherein correlation between topography and phase is significant and stable. When possible, our approach also takes advantage of any inherent redundancy provided by multiple interferograms constructed with common scenes. We define a unique set of component time intervals for a given suite of interferometric pairs. We estimate an internally consistent transfer function for each component time interval, which can then be recombined to correct any arbitrary interferometric pair. We demonstrate our approach on a synthetic example and on data from two locations: Long Valley Caldera, California, which experienced prolonged periods of surface deformation from pressurization of a deep magma chamber, and one coseismic interferogram from the 2007 Mw 7.8 Tocapilla earthquake in northern Chile. In both examples, the corrected interferograms show improvements in regions of high relief, independent of whether or not we pre‐correct the data for a source model. We believe that most of the remaining signals are predominately due to heterogeneous water vapor distribution that requires more sophisticated correction methods than those described here.Made available in DSpace on 2023-08-01T20:33:29Z (GMT). No. of bitstreams: 5 LSHMD10.pdf: 6094682 bytes, checksum: 923c3edf78214dc3a3265ca640daced4 (MD5) license_text: 21936 bytes, checksum: 9833653f73f7853880c94a6fead477b1 (MD5) license_url: 49 bytes, checksum: 4afdbb8c545fd630ea7db775da747b2f (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) license.txt: 4194 bytes, checksum: 7f2e2c17ef6585de66da58d1bfa8b5e1 (MD5) Previous issue date: 2010enengLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)Atmospheric delayMultiscale analysisInSARLong Valley CalderaTocopilla earthquakeA multiscale approach to estimating topographically correlated propagation delays in radar interferogramsPreprintinfo:eu-repo/semantics/preprintinfo:eu-repo/semantics/submittedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaMusé, PabloHetland, EricSimons, MarkLin, Yunung NinaDiCaprio, 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spellingShingle A multiscale approach to estimating topographically correlated propagation delays in radar interferograms
Musé, Pablo
Atmospheric delay
Multiscale analysis
InSAR
Long Valley Caldera
Tocopilla earthquake
status_str submittedVersion
title A multiscale approach to estimating topographically correlated propagation delays in radar interferograms
title_full A multiscale approach to estimating topographically correlated propagation delays in radar interferograms
title_fullStr A multiscale approach to estimating topographically correlated propagation delays in radar interferograms
title_full_unstemmed A multiscale approach to estimating topographically correlated propagation delays in radar interferograms
title_short A multiscale approach to estimating topographically correlated propagation delays in radar interferograms
title_sort A multiscale approach to estimating topographically correlated propagation delays in radar interferograms
topic Atmospheric delay
Multiscale analysis
InSAR
Long Valley Caldera
Tocopilla earthquake
url https://hdl.handle.net/20.500.12008/38722