Classification of ground deformation using sentinel-1 persistent scatterer interferometry time series
Displacement time series (TS) provides temporal and spatial information related to ground defor- mation. This study aims to investigate temporal behavior of ground deformation TS, including classification of displacement trends and periodicity evaluation, which ease the interpretation of movements....
| Autores: | , , , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/385855 |
| Acceso en línea: | https://hdl.handle.net/2117/385855 https://dx.doi.org/10.1080/15481603.2022.2030535 |
| Access Level: | acceso abierto |
| Palabra clave: | Remote sensing Seismology Natural disasters Ground motion service Time series Classification SAR PSI Sentinel-1 Teledetecció Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
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Classification of ground deformation using sentinel-1 persistent scatterer interferometry time seriesMirmazloumi, Seyed MohammadWassie, Yismaw Abera|||0000-0003-3756-1680Antonio Navarro, JosePalamá, RiccardoKrishnakumar, VrindaBarra, Anna|||0000-0001-6254-7931Cuevas-González, MaríaCrosetto, MicheleMonserrat Hernández, OriolRemote sensingSeismologyNatural disastersGround motion serviceTime seriesClassificationSARPSISentinel-1TeledeteccióÀrees temàtiques de la UPC::Enginyeria de la telecomunicacióDisplacement time series (TS) provides temporal and spatial information related to ground defor- mation. This study aims to investigate temporal behavior of ground deformation TS, including classification of displacement trends and periodicity evaluation, which ease the interpretation of movements. To this end, we propose several modifications to an existing automatic classification workflow of Persistent Scatterers Interferometry (PSI) TS using new tests to classify ground deformations into seven main trends: Stable, Linear, Quadratic, Bilinear, Phase Unwrapping Errors (PUE), Discontinuous with constant and different velocities. We illustrate our approach over 1500 km2 of the Granada region and the metropolitan area of Barcelona, which were monitored using Sentinel-1 images and a PSI technique. This study provided the spatial distribution of different ground movement types and was useful to detect several TS anomalies due to PUE. The proposed approach also identified stable targets, which were wrongly classified as moving scatterers by the existing classification method. A periodicity analysis was finally performed using the Welch’s power spectral density estimator to investigate seasonal and yearly fluctuations. The method was vali- dated using simulated data, where the classified TSs characterized by probable phase unwrapping errors were verified by PSI experts. The overall classification accuracy was 77.8%, indicating that the proposed method has a considerable TS classification potential.The work of S. Mohammad Mirmazloumi has been funded by the Spanish State Research Agency, through a grant for a pre-doctorate contract (Ref: PRE2018-083394). The work of Yismaw Wassie has been funded by AGAUR, Generalitat de Catalunya, through a grant for the recruitment of early- stage research staff (Ref: 2019 FI_B 00050). The processing of Granada has been funded by the project “RISKCOAST” (SOE3/P4/E0868) of the Interreg SUDOE Programme.Peer Reviewed20222022-02-0320232023-04-03journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/385855https://dx.doi.org/10.1080/15481603.2022.2030535reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3858552026-05-27T15:37:01Z |
| dc.title.none.fl_str_mv |
Classification of ground deformation using sentinel-1 persistent scatterer interferometry time series |
| title |
Classification of ground deformation using sentinel-1 persistent scatterer interferometry time series |
| spellingShingle |
Classification of ground deformation using sentinel-1 persistent scatterer interferometry time series Mirmazloumi, Seyed Mohammad Remote sensing Seismology Natural disasters Ground motion service Time series Classification SAR PSI Sentinel-1 Teledetecció Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
| title_short |
Classification of ground deformation using sentinel-1 persistent scatterer interferometry time series |
| title_full |
Classification of ground deformation using sentinel-1 persistent scatterer interferometry time series |
| title_fullStr |
Classification of ground deformation using sentinel-1 persistent scatterer interferometry time series |
| title_full_unstemmed |
Classification of ground deformation using sentinel-1 persistent scatterer interferometry time series |
| title_sort |
Classification of ground deformation using sentinel-1 persistent scatterer interferometry time series |
| dc.creator.none.fl_str_mv |
Mirmazloumi, Seyed Mohammad Wassie, Yismaw Abera|||0000-0003-3756-1680 Antonio Navarro, Jose Palamá, Riccardo Krishnakumar, Vrinda Barra, Anna|||0000-0001-6254-7931 Cuevas-González, María Crosetto, Michele Monserrat Hernández, Oriol |
| author |
Mirmazloumi, Seyed Mohammad |
| author_facet |
Mirmazloumi, Seyed Mohammad Wassie, Yismaw Abera|||0000-0003-3756-1680 Antonio Navarro, Jose Palamá, Riccardo Krishnakumar, Vrinda Barra, Anna|||0000-0001-6254-7931 Cuevas-González, María Crosetto, Michele Monserrat Hernández, Oriol |
| author_role |
author |
| author2 |
Wassie, Yismaw Abera|||0000-0003-3756-1680 Antonio Navarro, Jose Palamá, Riccardo Krishnakumar, Vrinda Barra, Anna|||0000-0001-6254-7931 Cuevas-González, María Crosetto, Michele Monserrat Hernández, Oriol |
| author2_role |
author author author author author author author author |
| dc.subject.none.fl_str_mv |
Remote sensing Seismology Natural disasters Ground motion service Time series Classification SAR PSI Sentinel-1 Teledetecció Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
| topic |
Remote sensing Seismology Natural disasters Ground motion service Time series Classification SAR PSI Sentinel-1 Teledetecció Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
| description |
Displacement time series (TS) provides temporal and spatial information related to ground defor- mation. This study aims to investigate temporal behavior of ground deformation TS, including classification of displacement trends and periodicity evaluation, which ease the interpretation of movements. To this end, we propose several modifications to an existing automatic classification workflow of Persistent Scatterers Interferometry (PSI) TS using new tests to classify ground deformations into seven main trends: Stable, Linear, Quadratic, Bilinear, Phase Unwrapping Errors (PUE), Discontinuous with constant and different velocities. We illustrate our approach over 1500 km2 of the Granada region and the metropolitan area of Barcelona, which were monitored using Sentinel-1 images and a PSI technique. This study provided the spatial distribution of different ground movement types and was useful to detect several TS anomalies due to PUE. The proposed approach also identified stable targets, which were wrongly classified as moving scatterers by the existing classification method. A periodicity analysis was finally performed using the Welch’s power spectral density estimator to investigate seasonal and yearly fluctuations. The method was vali- dated using simulated data, where the classified TSs characterized by probable phase unwrapping errors were verified by PSI experts. The overall classification accuracy was 77.8%, indicating that the proposed method has a considerable TS classification potential. |
| publishDate |
2022 |
| dc.date.none.fl_str_mv |
2022 2022-02-03 2023 2023-04-03 |
| dc.type.none.fl_str_mv |
journal article http://purl.org/coar/resource_type/c_6501 VoR http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| dc.type.openaire.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.none.fl_str_mv |
https://hdl.handle.net/2117/385855 https://dx.doi.org/10.1080/15481603.2022.2030535 |
| url |
https://hdl.handle.net/2117/385855 https://dx.doi.org/10.1080/15481603.2022.2030535 |
| dc.language.none.fl_str_mv |
Inglés eng |
| language_invalid_str_mv |
Inglés |
| language |
eng |
| dc.rights.none.fl_str_mv |
open access http://purl.org/coar/access_right/c_abf2 Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| dc.rights.openaire.fl_str_mv |
info:eu-repo/semantics/openAccess |
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open access http://purl.org/coar/access_right/c_abf2 Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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openAccess |
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application/pdf |
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reponame:UPCommons. Portal del coneixement obert de la UPC instname:Universitat Politècnica de Catalunya (UPC) |
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