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Orbit error removal in InSAR/MTInSAR with a patch-based polynomial model / Yanan Du in International journal of applied Earth observation and geoinformation, vol 102 (October 2021)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 102 (October 2021) . - n° 102438 Titre : Orbit error removal in InSAR/MTInSAR with a patch-based polynomial model Type de document : Article/Communication Auteurs : Yanan Du, Auteur ; Hai Qiang Fu, Auteur ; Lin Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 102438 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] image ALOS-PALSAR [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] interferométrie différentielle [Termes IGN] jeu de données [Termes IGN] modèle d'erreur [Termes IGN] orbitographie [Termes IGN] transformation polynomiale Résumé : (auteur) The orbit error caused by the inaccuracy of the orbit state vector can lead to fringes in differential interferograms, which can impede the estimation of deformation in differential SAR interferometry (DInSAR) applications. Usually, a set of polynomial coefficients for an entire SAR image is obtained for orbit error removal. However, the orbit error plane is influenced by overfitting in the case that the SAR satellites do not have a precise orbit. In this paper, a patch-based polynomial method is proposed to fit the orbit error plane. The new method divides an SAR image into several overlapping patches in the azimuth and range directions. Every patch obtains its own polynomial coefficients, and an iterative least-square method is used to mosaic the orbit plane. This method is tested and validated via a simulated dataset and then applied to ALOS1/2 PALSAR and Sentinel-1A datasets. The accuracy of deformation is evaluated by in situ GPS datasets. The results show that the patch-based method can fit the orbit phase plane more accurately than the traditional polynomial model with millimeter-level displacement improvement, especially in the margin areas of ALOS1/2 and for the wide-coverage Sentinel-1A datasets. Moreover, in the MTInSAR parameter calculations, the new method improves the accuracy of mean velocity calculations for ALOS1 time series, with a reduction of RMSE from 4.47 mm/yr to 3.17 mm/yr. Additionally, the new method reduces the spatial correlation of the residual topographic phase, with a mean value reduction from 0.32 m to 0.13 m. Numéro de notice : A2021-687 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article DOI : 10.1016/j.jag.2021.102438 En ligne : https://doi.org/10.1016/j.jag.2021.102438 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98419 [article]

Estimation of surface deformation due to Pasni earthquake using RADAR interferometry / Muhammad Ali in Geocarto international, vol 36 n° 14 ([01/08/2021])  

Public [article]  inGeocarto international > vol 36 n° 14 [01/08/2021] . - pp 1630 - 1645 Titre : Estimation of surface deformation due to Pasni earthquake using RADAR interferometry Type de document : Article/Communication Auteurs : Muhammad Ali, Auteur ; Muhammad Shahzad, Auteur ; Majir Nazeer, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1630 - 1645 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande C [Termes IGN] déformation de surface [Termes IGN] déformation verticale de la croute terrestre [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] Pakistan [Termes IGN] polarisation [Termes IGN] rapport signal sur bruit [Termes IGN] séisme [Termes IGN] série temporelle Résumé : (auteur) This study analyzed the land deformation associated with Mw 6.3 earthquake along Pasni coast, Pakistan. Post-earthquake widespread surface displacements were found using Sentinel-1 data. Pre, Co and Post-seismic images were used to investigate the deformation trends. Before the earthquake, 89.65% of Pasni land mass showed uplifting from 0.0 to 3.0 cm at 1.00 mm/day while 3.0 cm subsidence was noted in 86.36% of the land mass after the earthquake at 2.5 mm/day. However, two weeks after the earthquake, 72.9% Pasni land mass showed uplifting at an unprecedented rate of 3.3 mm/day. The maximum deformation along the Line Of Sight (LOS) direction in co-seismic time was about -4.0 cm. Azimuthal interferogram showed more complex displacement pattern with both negative and positive displacements between ±5.0 cm. Pasni is already facing many problems due to increased sea water intrusion under prevailing climatic changes and land deformation due to strong earthquakes. Numéro de notice : A2021-557 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1661031 date de publication en ligne : 09/09/2019 En ligne : https://doi.org/10.1080/10106049.2019.1661031 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98110 [article]

Glacier elevation change in the Western Qilian mountains as observed by TerraSAR-X/TanDEM-X images / Qibing Zhang in Geocarto international, vol 36 n° 12 ([01/07/2021])  

Public [article]  inGeocarto international > vol 36 n° 12 [01/07/2021] . - pp 1365-1377 Titre : Glacier elevation change in the Western Qilian mountains as observed by TerraSAR-X/TanDEM-X images Type de document : Article/Communication Auteurs : Qibing Zhang, Auteur ; Shichang Kang, Auteur Année de publication : 2021 Article en page(s) : pp 1365-1377 Note générale : Bibliothèque Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] altitude [Termes IGN] changement climatique [Termes IGN] détection de changement [Termes IGN] glacier [Termes IGN] interferométrie différentielle [Termes IGN] Kansou (Chine) [Termes IGN] MNS TerraSAR & TanDEM-X [Termes IGN] montagne [Termes IGN] précipitation [Termes IGN] température de l'air [Termes IGN] Tsinghai (Chine) Résumé : (Auteur) The glaciers in the Qilian mountains are a major water resource for the arid Hexi corridor and Qaidam basin. With the climate becoming warmer and wetter, it is essential to study the glacier elevation changes in this region. We used TerraSAR-X/TanDEM-X images, SRTM DEM data and differential synthetic aperture radar interferometry (DInSAR) technology to analyse the glacier elevation change. Results show that the glacier elevation is changing at the rate of –0.35 m yr−1 in the western Qilian mountains between 2000 and 2014. The glacier elevation thinning at –0.40 m yr−1 in the southern part of this region is more severe than that in the northern part (–0.29 m yr−1). The long-term equilibrium line altitude, calculated from glacier elevation change in each elevation bin, was at 5150 m, which is equal to that inferred from glacial area distribution in each elevation bin. Glacier shrinkage is related to air temperature increasing. Numéro de notice : A2021-378 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1648563 date de publication en ligne : 09/08/2019 En ligne : https://doi.org/10.1080/10106049.2019.1648563 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97876 [article]

Refinement of interferometric SAR parameters using digital terrain model as an external reference / Jyunpei Uemoto in ISPRS Journal of photogrammetry and remote sensing, vol 175 (May 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 175 (May 2021) . - pp 34 - 43 Titre : Refinement of interferometric SAR parameters using digital terrain model as an external reference Type de document : Article/Communication Auteurs : Jyunpei Uemoto, Auteur Année de publication : 2021 Article en page(s) : pp 34 - 43 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] ajustement de paramètres [Termes IGN] empreinte [Termes IGN] hauteur (coordonnée) [Termes IGN] hauteur des arbres [Termes IGN] hauteur du bâti [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] jeu de données [Termes IGN] modèle numérique de surface [Termes IGN] modèle numérique de terrain [Termes IGN] point d'appui [Termes IGN] radar aéroporté à visée latérale Résumé : (auteur) Numéro de notice : A2021-262 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.02.017 date de publication en ligne : 10/03/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.02.017 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97309 [article]

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Detecting ground deformation in the built environment using sparse satellite InSAR data with a convolutional neural network / Nantheera Anantrasirichai in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 4 (April 2021) . - pp 2940 - 2950 Titre : Detecting ground deformation in the built environment using sparse satellite InSAR data with a convolutional neural network Type de document : Article/Communication Auteurs : Nantheera Anantrasirichai, Auteur ; Juliet Biggs, Auteur ; Krisztina Kelevitz, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2940 - 2950 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] apprentissage automatique [Termes IGN] bati [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] complétion [Termes IGN] covariance [Termes IGN] déformation de la croute terrestre [Termes IGN] données d'apprentissage [Termes IGN] effet atmosphérique [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] interpolation spatiale [Termes IGN] matrice [Termes IGN] optimisation (mathématiques) [Termes IGN] représentation parcimonieuse [Termes IGN] Royaume-Uni [Termes IGN] zone urbaine Résumé : (auteur) The large volumes of Sentinel-1 data produced over Europe are being used to develop pan-national ground motion services. However, simple analysis techniques like thresholding cannot detect and classify complex deformation signals reliably making providing usable information to a broad range of nonexpert stakeholders a challenge. Here, we explore the applicability of deep learning approaches by adapting a pretrained convolutional neural network (CNN) to detect deformation in a national-scale velocity field. For our proof-of-concept, we focus on the U.K. where previously identified deformation is associated with coal-mining, ground water withdrawal, landslides, and tunneling. The sparsity of measurement points and the presence of spike noise make this a challenging application for deep learning networks, which involve calculations of the spatial convolution between images. Moreover, insufficient ground truth data exist to construct a balanced training data set, and the deformation signals are slower and more localized than in previous applications. We propose three enhancement methods to tackle these problems: 1) spatial interpolation with modified matrix completion; 2) a synthetic training data set based on the characteristics of the real U.K. velocity map; and 3) enhanced overwrapping techniques. Using velocity maps spanning 2015–2019, our framework detects several areas of coal mining subsidence, uplift due to dewatering, slate quarries, landslides, and tunnel engineering works. The results demonstrate the potential applicability of the proposed framework to the development of automated ground motion analysis systems. Numéro de notice : A2021-283 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-020-00323-6 date de publication en ligne : 31/08/2020 En ligne : https://doi.org/10.1007/s12518-020-00323-6 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97391 [article]

A soil texture categorization mapping from empirical and semi-empirical modelling of target parameters of synthetic aperture radar / Shoba Periasamy in Geocarto international, vol 36 n° 5 ([15/03/2021])  

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Comprehensive time-series analysis of bridge deformation using differential satellite radar interferometry based on Sentinel-1 / Matthias Schlögl in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)  

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Forest height estimation using a single-pass airborne L-band polarimetric and interferometric SAR system and tomographic techniques / Yue Huang in Remote sensing, Vol 13 n° 3 (February 2021)  

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Reclaimed-airport surface-deformation monitoring by improved permanent-scatterer interferometric synthetic-aperture radar: a case study of Shenzhen Bao'an international airport, China / Lu Miao in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 2 (February 2021)  

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Study of systematic bias in measuring surface deformation with SAR interferometry / Homa Ansari in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)  

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Flood mapping from radar remote sensing using automated image classification techniques / Lisa Landuyt (2021)  

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Remote sensing and GIS / Basudeb Bhatta (2021)

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Geostatistical analysis and mitigation of the atmospheric phase screens in Ku-band terrestrial radar interferometric observations of an alpine glacier / Simone Baffelli in IEEE Transactions on geoscience and remote sensing, vol 58 n° 11 (November 2020)  

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Combined InSAR and terrestrial structural monitoring of bridges / Sivasakthy Selvakumaran in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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Illuminating the spatio-temporal evolution of the 2008–2009 Qaidam earthquake sequence with the joint use of Insar time series and teleseismic data / Simon Daout in Remote sensing, vol 12 n° 17 (September 2020)  

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