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Orthorectification of full-polarimetric radarsat-2 data using accurate LIDAR DSM / Thierry Toutin in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)
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Titre : Orthorectification of full-polarimetric radarsat-2 data using accurate LIDAR DSM Type de document : Article/Communication Auteurs : Thierry Toutin , Auteur ; Huili Wang, Auteur ; Pierre Chomaz, Auteur ; Eric Pottier, Auteur
Année de publication : 2013 Article en page(s) : pp 5252 - 5258 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] correction géométrique
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] données polarimétriques
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] modèle numérique de surface
[Termes IGN] orthorectification automatique
[Termes IGN] polarimétrie radarRésumé : (Auteur) Orthorectification using digital terrain models is a key issue for full-polarimetric complex SAR data because resampling the complex data can corrupt the polarimetric phase, mainly in terrain with relief. This research thus compared two methods for the orthorectification of the complex SAR data: The polarimetric processing is performed before (image-space method) or after (ground-space method) the geometric processing. Radarsat-2 fine-quad data acquired with different look angles over a hilly relief study site were orthorectified using accurate light detection and ranging digital surface model. Quantitative evaluations between the two methods as a function of different geometric and radiometric parameters were thus performed to evaluate the impact during orthorectification. The results demonstrated that the look angles and the terrain slopes can potentially corrupt the polarimetric complex SAR data during its orthorectification with the ground-space method. In addition, general advice is provided to reduce these impacts to an acceptable level for the users and their polarimetric applications. Numéro de notice : A2013-695 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2233206 En ligne : https://doi.org/10.1109/TGRS.2012.2233206 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32831
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 12 (December 2013) . - pp 5252 - 5258[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013121 RAB Revue Centre de documentation En réserve L003 Disponible SAR image categorization with log cumulants of the fractional Fourier transform coefficients / Jagmal Singh in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)
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Titre : SAR image categorization with log cumulants of the fractional Fourier transform coefficients Type de document : Article/Communication Auteurs : Jagmal Singh, Auteur ; Mihai Dactu, Auteur Année de publication : 2013 Article en page(s) : pp 5273 - 5282 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] fractionnement
[Termes IGN] image radar moirée
[Termes IGN] image TanDEM-X
[Termes IGN] image TerraSAR-X
[Termes IGN] transformation de FourierRésumé : (Auteur) With the advent of high-resolution (HR) synthetic aperture radar (SAR) images from satellites like TerraSAR-X and TanDEM-X, interest is now on patch-oriented image categorization in contrast to the pixel-based classification in low-resolution SAR images. SAR image categorization requires the generation of a compact feature descriptor that accurately defines the content of the image patch under consideration. As phase information plays a critical role in SAR images, this paper proposes the use of a chirplet-derived transform, i.e., the fractional Fourier transform (FrFT), for generating a compact feature descriptor for single-look complex (SLC) SAR images. Representing a SAR signal in rotated joint time-frequency planes via the FrFT allows discovering the underlying backscattering phenomenon of the objects on the ground. SAR image projections on different planes of the joint time-frequency space using the FrFT provide a simple statistical response that is easier to analyze. The proposed method has been compared with a multiscale approach, i.e., Gabor filter banks, a second-order-statistics-based method (as gray-level co-occurrence matrices), and a spectral descriptor method. We demonstrate the suitability of the FrFT-based method for image categorization on the basis of backscattering behavior, whereas the Gabor-filter-bank-based method is found mainly suitable for images with a strong texture. This paper demonstrates enhancement in the separability for most of the considered categories when using logarithmic cumulants instead of linear moments for both the FrFT-based and Gabor-filter-bank-based methods. The experimental database consists of 2000 image patches (of size 200 200 pixels) extracted from SLC HR TerraSAR-X scenes. Numéro de notice : A2013-697 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2230892 En ligne : https://doi.org/10.1109/TGRS.2012.2230892 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32833
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 12 (December 2013) . - pp 5273 - 5282[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013121 RAB Revue Centre de documentation En réserve L003 Disponible The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques / Chengbin Deng in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)
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Titre : The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques Type de document : Article/Communication Auteurs : Chengbin Deng, Auteur ; Changshan Wu, Auteur Année de publication : 2013 Article en page(s) : pp 100 - 110 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] apprentissage automatique
[Termes IGN] image multibande
[Termes IGN] image Terra-MODIS
[Termes IGN] méthode des moindres carrés
[Termes IGN] surface imperméable
[Termes IGN] zone urbaineRésumé : (Auteur) Urban impervious surface information is essential for urban and environmental applications at the regional/national scales. As a popular image processing technique, spectral mixture analysis (SMA) has rarely been applied to coarse-resolution imagery due to the difficulty of deriving endmember spectra using traditional endmember selection methods, particularly within heterogeneous urban environments. To address this problem, we derived endmember signatures through a least squares solution (LSS) technique with known abundances of sample pixels, and integrated these endmember signatures into SMA for mapping large-scale impervious surface fraction. In addition, with the same sample set, we carried out objective comparative analyses among SMA (i.e. fully constrained and unconstrained SMA) and machine learning (i.e. Cubist regression tree and Random Forests) techniques. Analysis of results suggests three major conclusions. First, with the extrapolated endmember spectra from stratified random training samples, the SMA approaches performed relatively well, as indicated by small MAE values. Second, Random Forests yields more reliable results than Cubist regression tree, and its accuracy is improved with increased sample sizes. Finally, comparative analyses suggest a tentative guide for selecting an optimal approach for large-scale fractional imperviousness estimation: unconstrained SMA might be a favorable option with a small number of samples, while Random Forests might be preferred if a large number of samples are available. Numéro de notice : A2013-705 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32841
in ISPRS Journal of photogrammetry and remote sensing > vol 86 (December 2013) . - pp 100 - 110[article]Wavelet-Based Compressed Sensing for SAR Tomography of Forested Areas / Esteban Aguilera in IEEE Transactions on geoscience and remote sensing, vol 51 n° 12 (December 2013)
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Titre : Wavelet-Based Compressed Sensing for SAR Tomography of Forested Areas Type de document : Article/Communication Auteurs : Esteban Aguilera, Auteur ; Matteo Nannini, Auteur ; Andreas Reigber, Auteur Année de publication : 2013 Article en page(s) : pp 5283 - 5295 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Allemagne
[Termes IGN] bande L
[Termes IGN] compression par ondelettes
[Termes IGN] données polarimétriques
[Termes IGN] forêt
[Termes IGN] image E-SAR
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] polarimétrie radar
[Termes IGN] tomographie radarRésumé : (Auteur) Synthetic aperture radar (SAR) tomography is a 3-D imaging modality that is commonly tackled by spectral estimation techniques. Thus, the backscattered power along the cross-range direction can be readily obtained by computing the Fourier spectrum of a stack of multibaseline measurements. In addition, recent work has addressed the tomographic inversion under the framework of compressed sensing, thereby recovering sparse cross-range profiles from a reduced set of measurements. This paper differs from previous publications, in that it focuses on sparse expansions in the wavelet domain while working with the second-order statistics of the corresponding multibaseline measurements. In this regard, we elaborate on the conditions under which this perspective is applicable to forested areas and discuss the possibility of optimizing the acquisition geometry. Finally, we compare this approach with traditional nonparametric ones and validate it by using fully polarimetric L-band data acquired by the Experimental SAR (E-SAR) sensor of the German Aerospace Center (DLR). Numéro de notice : A2013-696 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2231081 En ligne : https://doi.org/10.1109/TGRS.2012.2231081 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32832
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 12 (December 2013) . - pp 5283 - 5295[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013121 RAB Revue Centre de documentation En réserve L003 Disponible A combined object- and pixel-based image analysis framework for urban land cover classification of VHR imagery / Bahram Salehi in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 11 (November 2013)
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Titre : A combined object- and pixel-based image analysis framework for urban land cover classification of VHR imagery Type de document : Article/Communication Auteurs : Bahram Salehi, Auteur ; Yun Zhang, Auteur ; Ming Zhong, Auteur Année de publication : 2013 Article en page(s) : pp 999 - 1014 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image Ikonos
[Termes IGN] image Quickbird
[Termes IGN] image Worldview
[Termes IGN] Nouveau-Brunswick (Canada)
[Termes IGN] occupation du sol
[Termes IGN] segmentation d'image
[Termes IGN] transformation en ondelettesRésumé : (Auteur) This paper aims at exploiting the advantages of pixel-based and object-based image analysis approaches for urban land cover classification of very high resolution ( VHR ) satellite imagery through a combined object- and pixel-based image analysis framework. The framework starts with segmenting the image resulting in several spectral and spatial features of segments. To overcome the curse of dimensionality, a wavelet- based feature extraction method is proposed to reduce the number of features. The wavelet-based method is automatic, fast, and can preserve local variations in objects' spectral/ spatial signatures. Finally, the extracted features together with the original bands of the image are classified using the conventional pixel-based Maximum Likelihood classification. The proposed method was tested on the WorldView-2, QuickBird, and Ikonos images of the same urban area for comparison purposes. Results show up to 17 percent, 10 percent, and 11 percent improvement in kappa coefficients compared to the case in which only the original bands of the image are used for WV - 2 , QB , and IK , respectively. Furthermore, the objects' spectral features contribute more to increasing classification accuracy than spatial features. Numéro de notice : A2013-596 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.79.11.999 En ligne : https://doi.org/10.14358/PERS.79.11.999 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32732
in Photogrammetric Engineering & Remote Sensing, PERS > vol 79 n° 11 (November 2013) . - pp 999 - 1014[article]Developing an object-based hyperspatial image classifier with a case study using WorldView-2 data / Harini Sridharan in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 11 (November 2013)
PermalinkLandscape metrics for analysing urbanization-induced land use and land cover changes / Hua Liu in Geocarto international, vol 28 n° 7-8 (November - December 2013)
PermalinkMapping and assessing of urban impervious areas using multiple endmember spectral mixture analysis: a case study in the city of Tampa, Florida / Fenqing Weng in Geocarto international, vol 28 n° 7-8 (November - December 2013)
PermalinkMarkov land cover change modeling using pairs of time-series satellite images / Priyakant Sinha in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 11 (November 2013)
PermalinkParcel-level identification of crop types using different classification algorithms and multi-resolution imagery in southeastern Turkey / Ugur Alganci in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 11 (November 2013)
PermalinkProvenance capture and use in a satellite data processing pipeline / Scott Jensen in IEEE Transactions on geoscience and remote sensing, vol 51 n° 11 (November 2013)
PermalinkA semi-ellipsoid-model based fuzzy classifier to map grassland in Inner Mongolia, China / Hai Lan in ISPRS Journal of photogrammetry and remote sensing, vol 85 (November 2013)
PermalinkA spectral gradient difference based approach for land cover change detection / Jun Chen in ISPRS Journal of photogrammetry and remote sensing, vol 85 (November 2013)
PermalinkLa télédétection au service des études urbaines : expansion de la ville de Pondichéry entre 1973 et 2009 / Emilien Kieffer in Géomatique expert, n° 95 (01/11/2013)
PermalinkThe new inteligence / Jonathan Shears in GEO: Geoconnexion international, vol 12 n° 10 (november – december 2013)
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