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A feature based change detection approach using multi-scale orientation for multi-temporal SAR images / R. Vijaya Geetha in European journal of remote sensing, vol 54 sup 2 (2021)
[article]
Titre : A feature based change detection approach using multi-scale orientation for multi-temporal SAR images Type de document : Article/Communication Auteurs : R. Vijaya Geetha, Auteur ; S. Kalaivani, Auteur Année de publication : 2021 Article en page(s) : pp 248 - 264 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse de groupement
[Termes IGN] anisotropie
[Termes IGN] chatoiement
[Termes IGN] classification non dirigée
[Termes IGN] classification par nuées dynamiques
[Termes IGN] détection de changement
[Termes IGN] filtre de Gabor
[Termes IGN] image multitemporelle
[Termes IGN] image radar moirée
[Termes IGN] matrice de confusion
[Termes IGN] transformation en ondelettesRésumé : (auteur) Excellent operation regardless of weather conditions and superior resolution independent of sensor light are the most attractive and desired features of synthetic aperture radar (SAR) imagery. This paper proposes an exclusive multi-scale with multiple orientation approach for multi-temporal SAR images. This approach integrates pre-processing and change detection. Pre-processing is performed on the SAR imagery through speckle reducing anisotropic diffusion and discrete wavelet transform. The processed speckle-free images are designed by Log-Gabor filter bank in terms of multi-scale with multiple orientations. The maximum magnitude of multiple orientations is concatenated to obtain feature-based scale representation. Each scale is dealt with multiple orientations and is compared by band-wise subtraction to retrieve difference image (DI) coefficient. The series of the difference coefficients from each scale are add-on together to estimate a DI. Thus, the resultant image of multi-scale orientation gives perception of detailed information with specific contour. Constrained k-means clustering algorithm is preferred to achieve change and un-change map. Performance of the proposed approach is validated on three real SAR image datasets. The effective change detection is examined by using confusion matrix parameters. Experimental results are described to show the efficacy of the proposed approach. Numéro de notice : A2021-819 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2020.1759457 Date de publication en ligne : 12/06/2020 En ligne : https://doi.org/10.1080/22797254.2020.1759457 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98924
in European journal of remote sensing > vol 54 sup 2 (2021) . - pp 248 - 264[article]Investigation of the landslides in Beylikdüzü-Esenyurt districts of Istanbul from InSAR and GNSS observations / Caglar Bayik in Natural Hazards, vol 109 n° 1 (October 2021)
[article]
Titre : Investigation of the landslides in Beylikdüzü-Esenyurt districts of Istanbul from InSAR and GNSS observations Type de document : Article/Communication Auteurs : Caglar Bayik, Auteur ; Saygin Abdikan, Auteur ; Alpay Ozdemir, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1201 - 1220 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse diachronique
[Termes IGN] bande C
[Termes IGN] bande L
[Termes IGN] données géologiques
[Termes IGN] données GNSS
[Termes IGN] effondrement de terrain
[Termes IGN] image ALOS
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] Istanbul (Turquie)
[Termes IGN] surveillance géologique
[Termes IGN] urbanisationRésumé : (auteur) This study aims to detect recent landslide displacements caused by geological structure of the region where there is intense urbanization using advanced Interferometric Synthetic Aperture Radar (InSAR) techniques and with Global Navigation Satellite Systems (GNSS) observations in the Beylikdüzü and Esenyurt districts in Istanbul megacity, Turkey. In this study, multiple satellites with different frequencies (C-band, L-band) and periodic GNSS observations were employed. For the entire peninsula, we processed 149 images from the ascending orbit, 144 images from the descending orbit of Sentinel-1 (C-Band) and 24 ALOS-2 (L-band) images from the ascending orbit. The evaluations were carried out in the period between 2015 and 2020 for Sentinel-1 imagery and 2015–2020 for ALOS-2 imagery respectively. Since the study area is covered by dense settlements, the Persistent Scatterer InSAR (PSI) technique was utilized to determine the landslide behaviors. According to the results, for both orbits of the Sentinel-1, the horizontal displacement and the vertical displacement were observed in the range of − 10 to 6 mm. Compared to the magnitude of displacement signal measured by Sentinel-1, ALOS-2 data has higher values due to the high surface penetration of the L-band. The results showed that most of the old landslide regions are reactivated. Horizontal movement derived through Sentinel-1 showed that the highest movement overlaps with old landslides. L-band ALOS-2 provided better spatial coverage of landslide movement than C-band Sentinel-1 data, especially at the rural Numéro de notice : A2021-752 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT/URBANISME Nature : Article DOI : 10.1007/s11069-021-04875-7 Date de publication en ligne : 20/06/2021 En ligne : https://doi.org/10.1007/s11069-021-04875-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98737
in Natural Hazards > vol 109 n° 1 (October 2021) . - pp 1201 - 1220[article]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)
[article]
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 polynomialeRésumé : (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 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
in International journal of applied Earth observation and geoinformation > vol 102 (October 2021) . - n° 102438[article]Phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation / Peng Liu in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)
[article]
Titre : Phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation Type de document : Article/Communication Auteurs : Peng Liu, Auteur ; Zhenhong Li, Auteur ; Shisheng Wang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 14 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] chevauchement
[Termes IGN] Chine
[Termes IGN] discontinuité
[Termes IGN] image radar moirée
[Termes IGN] image TerraSAR-X
[Termes IGN] modèle numérique de surface
[Termes IGN] ombre
[Termes IGN] segmentation
[Termes IGN] semis de pointsRésumé : (auteur) Staring spotlight images with a spatial resolution of up to tens of centimeters are good data sources for urban applications including displacement mapping. However, phase discontinuities, layover, and shadowing effect are also associated with staring spotlight interferograms, adding to the difficulties in height estimation and spatial phase unwrapping. The scattering mechanism of the staring spotlight images in the urban environment is complicated, thus it is difficult to simulate and remove the reference height of staring spotlight interferograms directly. In addition, global spatial phase unwrapping networks tend to smooth phase discontinuities. With the aim of implementing height estimation and phase unwrapping for TerraSAR-X Staring Spotlight interferograms, a workflow for phase unmixing of TerraSAR-X staring spotlight interferograms is proposed in this paper. The PS height is estimated in the baseline domain rather than the spatial domain. Taking into account the length and height change of each connection, the spatial phase unwrapping network is adjusted and segmented into isolated networks. The connected components of the adjusted spatial phase unwrapping network can be identified using graph theory. Spatial phase unwrapping is implemented in individual networks. The unfolded height phase is separated from the unwrapped phase, and the remaining phase is deformation dominated. Compared with the traditional global spatial phase unwrapping method, this study demonstrates the feasibility of the proposed least squares parameter search and graph partition based workflow in urban area, for phase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation, as evidenced by external LiDAR DSM and temperature records. Numéro de notice : A2021-652 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.08.007 Date de publication en ligne : 14/08/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.08.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98382
in ISPRS Journal of photogrammetry and remote sensing > vol 180 (October 2021) . - pp 14 - 28[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2021101 SL Revue Centre de documentation Revues en salle Disponible 081-2021103 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021102 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Coniferous and broad-leaved forest distinguishing using L-band polarimetric SAR data / Fang Shang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)
[article]
Titre : Coniferous and broad-leaved forest distinguishing using L-band polarimetric SAR data Type de document : Article/Communication Auteurs : Fang Shang, Auteur ; Taiga Saito, Auteur ; Saya Ohi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 7487 - 7499 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] détection de changement
[Termes IGN] détection de cible
[Termes IGN] distribution spatiale
[Termes IGN] forêt de feuillus
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar moirée
[Termes IGN] Japon
[Termes IGN] Pinophyta
[Termes IGN] polarimétrie radarRésumé : (auteur) This article proposes a coniferous and broad-leaved forest distinguishing method using L-band polarimetric SAR data based on the structure-orientation parameter. The structure-orientation parameter is one of the averaged Stokes vector-based discriminators which is sensitive to the composition of equivalent horizontal and vertical structures. In the proposed method, the structure-orientation parameters is compensated by employing the scattered power information to remove the influence of the topography. The final distinguishing result is generated based on the statistical feature of the compensated parameters. The experiments using several sets of ALOS2-PALSAR2 level 1.1 data prove that the proposed method has high performance for forest-type distinguishing. Numéro de notice : A2021-648 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3032468 Date de publication en ligne : 03/11/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3032468 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98355
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 9 (September 2021) . - pp 7487 - 7499[article]A deep translation (GAN) based change detection network for optical and SAR remote sensing images / Xinghua Li in ISPRS Journal of photogrammetry and remote sensing, vol 179 (September 2021)PermalinkVariational bayesian compressive multipolarization indoor radar imaging / Van Ha Tang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)PermalinkEstimation of surface deformation due to Pasni earthquake using RADAR interferometry / Muhammad Ali in Geocarto international, vol 36 n° 14 ([01/08/2021])PermalinkRapid and large-scale mapping of flood inundation via integrating spaceborne synthetic aperture radar imagery with unsupervised deep learning / Xin Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)PermalinkUnsupervised denoising for satellite imagery using wavelet directional cycleGAN / Shaoyang Kong in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 2021)PermalinkSemantic unsupervised change detection of natural land cover with multitemporal object-based analysis on SAR images / Donato Amitrano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)PermalinkForest height estimation from a robust TomoSAR method in the case of small tomographic aperture with airborne dataset at L-band / Xing Peng in Remote sensing, vol 13 n° 11 (June-1 2021)PermalinkModel-based estimation of forest canopy height and biomass in the Canadian boreal forest using radar, LiDAR, and optical remote sensing / Michael L. Benson in IEEE Transactions on geoscience and remote sensing, vol 59 n° 6 (June 2021)PermalinkPolSAR ship detection based on neighborhood polarimetric covariance matrix / Tao Liu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 6 (June 2021)PermalinkSpatio-temporal linking of multiple SAR satellite data from medium and high resolution Radarsat-2 images / Bin Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)PermalinkA Bayesian displacement field approach to accurate registration of SAR images / Mingtao Ding in Geocarto international, vol 36 n° 9 ([15/05/2021])PermalinkForest height retrieval using P-band airborne multi-baseline SAR data: A novel phase compensation method / Hongliang Lu in ISPRS Journal of photogrammetry and remote sensing, vol 175 (May 2021)PermalinkLearning from multimodal and multitemporal earth observation data for building damage mapping / Bruno Adriano in ISPRS Journal of photogrammetry and remote sensing, vol 175 (May 2021)PermalinkLifting scheme-based sparse density feature extraction for remote sensing target detection / Ling Tian in Remote sensing, vol 13 n° 9 (May-1 2021)PermalinkSAR speckle removal using hybrid frequency modulations / Shuaiqi Liu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 5 (May 2021)PermalinkLeaf area index estimation of wheat crop using modified water cloud model from the time-series SAR and optical satellite data / Vijay Pratap Yadav in Geocarto international, vol 36 n° 7 ([15/04/2021])PermalinkDetecting 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)PermalinkExtraction of sea ice cover by Sentinel-1 SAR based on support vector machine with unsupervised generation of training data / Xiao-Ming Li in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)PermalinkGraph convolutional networks by architecture search for PolSAR image classification / Hongying Liu in Remote sensing, vol 13 n° 7 (April-1 2021)PermalinkTime-series snowmelt detection over the Antarctic using Sentinel-1 SAR images on Google Earth Engine / Dong Liang in Remote sensing of environment, Vol 256 (April 2020)Permalink