The Constrained-Network Propagation (C-NetP) Technique to Improve SBAS-DInSAR Deformation Time Series Retrieval
We present an innovative region-growing-based technique that permits to improve the surface displacement time-series retrieval capability of the two-scale Small BAseline Subset (SBAS) Differential Interferometric Synthetic Aperture Radar (DInSAR) approach in medium-to-low coherence regions. Starting...
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| Format: | Article |
| Language: | English |
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IEEE
2015-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/7312913/ |
| _version_ | 1818647850067689472 |
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| author | Chandrakanta Ojha Michele Manunta Riccardo Lanari Antonio Pepe |
| author_facet | Chandrakanta Ojha Michele Manunta Riccardo Lanari Antonio Pepe |
| author_sort | Chandrakanta Ojha |
| collection | DOAJ |
| description | We present an innovative region-growing-based technique that permits to improve the surface displacement time-series retrieval capability of the two-scale Small BAseline Subset (SBAS) Differential Interferometric Synthetic Aperture Radar (DInSAR) approach in medium-to-low coherence regions. Starting from a sequence of multitemporal differential SAR interferograms, computed at the full spatial resolution scale, the developed method “propagates” the information on the deformation relevant to a set of high coherent SAR pixels [referred to as source pixels (SPs)], in correspondence to which SBAS-DInSAR deformation measurements have previously been estimated, to their less coherent neighbouring ones. In this framework, a minimum-norm constrained optimization problem, relying on the use of constrained Delaunay triangulations (CDTs), is solved, where the constraints represent the displacement values at the SP locations. Such DInSAR processing scheme, referred to as Constrained-Network Propagation (C-NetP), is easy to implement and, although specifically developed to work within the two-scale SBAS framework, it can be extended to wider DInSAR scenarios. The validity of the method has been investigated by processing a SAR dataset acquired over the city of Rome (Italy) by the Cosmo-SkyMed constellation from July 2010 to October 2012. The achieved results demonstrate that the proposed C-NetP method is capable to significantly increase the spatial density of the SBAS-DInSAR measurements, reaching an improvement of about 250%. Such an improvement allows revealing deformation patterns that are partially or completely hidden, by applying the conventional two-scale SBAS processing. This is particularly relevant in urban areas where the assessment and management of the risk associated to the deformation affecting infrastructures is strategic for decision makers and local authorities. |
| first_indexed | 2024-12-17T01:09:05Z |
| format | Article |
| id | doaj.art-96938b7222cb40b0844cbda6e527313d |
| institution | Directory Open Access Journal |
| issn | 2151-1535 |
| language | English |
| last_indexed | 2024-12-17T01:09:05Z |
| publishDate | 2015-01-01 |
| publisher | IEEE |
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| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj.art-96938b7222cb40b0844cbda6e527313d2022-12-21T22:09:11ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352015-01-018104910492110.1109/JSTARS.2015.24823587312913The Constrained-Network Propagation (C-NetP) Technique to Improve SBAS-DInSAR Deformation Time Series RetrievalChandrakanta Ojha0Michele Manunta1Riccardo Lanari2Antonio Pepe3Istituto per il Rilevamento Elettromagnetico dell’Ambiente (IREA), National Council of Research (CNR), Naples, NA, ItalyIstituto per il Rilevamento Elettromagnetico dell’Ambiente (IREA), National Council of Research (CNR), Naples, NA, ItalyIstituto per il Rilevamento Elettromagnetico dell’Ambiente (IREA), National Council of Research (CNR), Naples, NA, ItalyIstituto per il Rilevamento Elettromagnetico dell’Ambiente (IREA), National Council of Research (CNR), Naples, NA, ItalyWe present an innovative region-growing-based technique that permits to improve the surface displacement time-series retrieval capability of the two-scale Small BAseline Subset (SBAS) Differential Interferometric Synthetic Aperture Radar (DInSAR) approach in medium-to-low coherence regions. Starting from a sequence of multitemporal differential SAR interferograms, computed at the full spatial resolution scale, the developed method “propagates” the information on the deformation relevant to a set of high coherent SAR pixels [referred to as source pixels (SPs)], in correspondence to which SBAS-DInSAR deformation measurements have previously been estimated, to their less coherent neighbouring ones. In this framework, a minimum-norm constrained optimization problem, relying on the use of constrained Delaunay triangulations (CDTs), is solved, where the constraints represent the displacement values at the SP locations. Such DInSAR processing scheme, referred to as Constrained-Network Propagation (C-NetP), is easy to implement and, although specifically developed to work within the two-scale SBAS framework, it can be extended to wider DInSAR scenarios. The validity of the method has been investigated by processing a SAR dataset acquired over the city of Rome (Italy) by the Cosmo-SkyMed constellation from July 2010 to October 2012. The achieved results demonstrate that the proposed C-NetP method is capable to significantly increase the spatial density of the SBAS-DInSAR measurements, reaching an improvement of about 250%. Such an improvement allows revealing deformation patterns that are partially or completely hidden, by applying the conventional two-scale SBAS processing. This is particularly relevant in urban areas where the assessment and management of the risk associated to the deformation affecting infrastructures is strategic for decision makers and local authorities.https://ieeexplore.ieee.org/document/7312913/Constrained optimization problemsdeformationDelaunay triangulationsDifferential Interferometric Synthetic Aperture Radar (DInSAR)Small BAseline Subset (SBAS)time series |
| spellingShingle | Chandrakanta Ojha Michele Manunta Riccardo Lanari Antonio Pepe The Constrained-Network Propagation (C-NetP) Technique to Improve SBAS-DInSAR Deformation Time Series Retrieval IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Constrained optimization problems deformation Delaunay triangulations Differential Interferometric Synthetic Aperture Radar (DInSAR) Small BAseline Subset (SBAS) time series |
| title | The Constrained-Network Propagation (C-NetP) Technique to Improve SBAS-DInSAR Deformation Time Series Retrieval |
| title_full | The Constrained-Network Propagation (C-NetP) Technique to Improve SBAS-DInSAR Deformation Time Series Retrieval |
| title_fullStr | The Constrained-Network Propagation (C-NetP) Technique to Improve SBAS-DInSAR Deformation Time Series Retrieval |
| title_full_unstemmed | The Constrained-Network Propagation (C-NetP) Technique to Improve SBAS-DInSAR Deformation Time Series Retrieval |
| title_short | The Constrained-Network Propagation (C-NetP) Technique to Improve SBAS-DInSAR Deformation Time Series Retrieval |
| title_sort | constrained network propagation c netp technique to improve sbas dinsar deformation time series retrieval |
| topic | Constrained optimization problems deformation Delaunay triangulations Differential Interferometric Synthetic Aperture Radar (DInSAR) Small BAseline Subset (SBAS) time series |
| url | https://ieeexplore.ieee.org/document/7312913/ |
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