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Material reflectance retrieval in urban tree shadows with physics-based empirical atmospheric correction / Karine R.M. Adeline (2013)
Titre : Material reflectance retrieval in urban tree shadows with physics-based empirical atmospheric correction Type de document : Article/Communication Auteurs : Karine R.M. Adeline, Auteur ; Nicolas Paparoditis , Auteur ; Jean-Philippe Gastellu-Etchegorry, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2013 Conférence : JURSE 2013, Joint Urban Remote Sensing Event 21/04/2013 23/04/2013 Sao Paulo Brésil Proceedings IEEE Importance : pp 279 - 283 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] arbre urbain
[Termes IGN] correction atmosphérique
[Termes IGN] houppier
[Termes IGN] image hyperspectrale
[Termes IGN] milieu urbain
[Termes IGN] modélisation 3D
[Termes IGN] ombre
[Termes IGN] rayonnement incident
[Termes IGN] rayonnement solaire
[Termes IGN] réflectance végétaleRésumé : (auteur) Material reflectance retrieval from high spatial resolution acquisitions over urban areas requires an accurate modeling of the signal accounting for the 3D environment. Especially in tree shadows, the solar radiation incident to the ground contributing to the estimation of the reflectance has many origins linked to the plant structure and its composition. In this paper, the 3D atmospheric correction code, ICARE, limited to opaque structures like buildings, is improved thanks to an empirical correction factor taking into account the porosity of a tree crown. The validation of this method is assessed through a dataset combining a hyperspectral image and a 3D model of the scene. Numéro de notice : C2013-006 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication DOI : 10.1109/JURSE.2013.6550719 Date de publication en ligne : 01/07/2013 En ligne : http://dx.doi.org/10.1109/JURSE.2013.6550719 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80181 A new technique using infrared satellite measurements to improve the accuracy of the CALIPSO cloud-aerosol discrimination method / A. Naeger in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 2 (January 2013)
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Titre : A new technique using infrared satellite measurements to improve the accuracy of the CALIPSO cloud-aerosol discrimination method Type de document : Article/Communication Auteurs : A. Naeger, Auteur ; S. Christopher, Auteur ; R. Ferrare, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 642 - 653 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] aérosol
[Termes IGN] analyse discriminante
[Termes IGN] image Aqua-MODIS
[Termes IGN] image infrarouge
[Termes IGN] image MSG-SEVIRI
[Termes IGN] image Terra-MODIS
[Termes IGN] nuage
[Termes IGN] Sahara, désert du
[Termes IGN] température de luminance
[Termes IGN] tempête de poussièreRésumé : (Auteur) In this paper, we develop a new technique called the brightness temperature difference cloud and aerosol discrimination algorithm (BTD CAD) that uses thermal infrared satellite measurements to improve the accuracy of the cloud-aerosol lidar and infrared pathfinder satellite observations (CALIPSO) CAD algorithm. It has been shown that the CALIPSO CAD algorithm can misclassify dense dust as cloud because the CALIPSO two-wavelength backscatter lidar operates at 532 and 1064 nm where very similar scattering properties are known to exist between dense dust and cloud. Therefore, we use the 11 and 12 um thermal infrared channels from both the moderate resolution imaging spectroradiometer (MODIS) and the spinning enhanced visible and infrared imager (SEVIRI), which are very sensitive to dust concentration, in order to reduce the frequency of the dust misclassifications encountered by the CALIPSO CAD algorithm. For the two Saharan dust events presented in this paper, both the MODIS and SEVIRI BTD CAD techniques performed well but the MODIS BTD CAD correctly reclassified more CALIPSO CAD misclassifications as dust. After applying both techniques to all the daytime CALIPSO transects over North Africa during June 2007, the MODIS and SEVIRI BTD CAD increased the total number of detected aerosol layers by approximately 10% and 4%, respectively. Even though the Version 3 (V3) CAD algorithm is significantly more accurate in deciphering between dense dust and clouds than the Version 2 algorithm, the V3 still showed some dust misclassifications among the case studies. Thus, the BTD CAD technique can help reduce the frequency of dust misclassifications encountered by the V3 CAD algorithm. Numéro de notice : A2013-020 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2196437 En ligne : https://doi.org/10.1109/TGRS.2012.2196437 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32158
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 1 Tome 2 (January 2013) . - pp 642 - 653[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013011B RAB Revue Centre de documentation En réserve L003 Disponible A review of EO image information mining / M. Quartilly in ISPRS Journal of photogrammetry and remote sensing, vol 75 (January 2013)
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Titre : A review of EO image information mining Type de document : Article/Communication Auteurs : M. Quartilly, Auteur ; I. Olaizola, Auteur Année de publication : 2013 Article en page(s) : pp 11 - 28 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] exploration de données
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] observation de la Terre
[Termes IGN] requête spatiale
[Termes IGN] spécificationRésumé : (Auteur) We analyze the state of the art of content-based retrieval in Earth observation image archives focusing on complete systems showing promise for operational implementation. The different paradigms at the basis of the main system families are introduced. The approaches taken are considered, focusing in particular on the phases after primitive feature extraction. The solutions envisaged for the issues related to feature simplification and synthesis, indexing, semantic labeling are reviewed. The methodologies for query specification and execution are evaluated. Conclusions are drawn on the state of published research in Earth observation (EO) mining. Numéro de notice : A2013-029 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.09.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32167
in ISPRS Journal of photogrammetry and remote sensing > vol 75 (January 2013) . - pp 11 - 28[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2013011 RAB Revue Centre de documentation En réserve L003 Disponible Semisupervised learning of hyperspectral data with unknown land-cover classes / G. Jun in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)
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Titre : Semisupervised learning of hyperspectral data with unknown land-cover classes Type de document : Article/Communication Auteurs : G. Jun, Auteur ; J. Ghosh, Auteur Année de publication : 2013 Article en page(s) : pp 273 - 282 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage semi-dirigé
[Termes IGN] Botswana
[Termes IGN] classification bayesienne
[Termes IGN] image hyperspectrale
[Termes IGN] occupation du sol
[Termes IGN] régression
[Termes IGN] réponse spectrale
[Termes IGN] variationRésumé : (Auteur) Both supervised and semisupervised algorithms for hyperspectral data analysis typically assume that all unlabeled data belong to the same set of land-cover classes that is represented by labeled data. This is not true in general, however, since there may be new classes in the unexplored regions within an image or in areas that are geographically near but topographically distinct. This problem is more likely to occur when one attempts to build classifiers that cover wider areas; such classifiers also need to address spatial variations in acquired spectral signatures if they are to be accurate and robust. This paper presents a semisupervised spatially adaptive mixture model (SESSAMM) to identify land covers from hyperspectral images in the presence of previously unknown land-cover classes and spatial variation of spectral responses. SESSAMM uses a nonparametric Bayesian framework to apply spatially adaptive mechanisms to the mixture model with (potentially) infinitely many components. In this method, each component in the mixture has spatially adapted parameters estimated by Gaussian process regression, and spatial correlations between indicator variables are also considered. The proposed SESSAMM algorithm is applied to hyperspectral data from Botswana and from the DC Mall, where some classes are present only in the unlabeled data. SESSAMM successfully differentiates unlabeled instances of previously known classes from unknown classes and provides better results than the standard Dirichlet process mixture model and other alternatives. Numéro de notice : A2013-014 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2198654 En ligne : https://doi.org/10.1109/TGRS.2012.2198654 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32152
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 1 Tome 1 (January 2013) . - pp 273 - 282[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013011A RAB Revue Centre de documentation En réserve L003 Disponible Semisupervised local discriminant analysis for feature extraction in hyperspectral images / W. Liao in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)
[article]
Titre : Semisupervised local discriminant analysis for feature extraction in hyperspectral images Type de document : Article/Communication Auteurs : W. Liao, Auteur ; A. Pizurica, Auteur ; Paul Scheunders, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 184 - 198 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse discriminante
[Termes IGN] classification semi-dirigée
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image hyperspectrale
[Termes IGN] matriceRésumé : (Auteur) We propose a novel semisupervised local discriminant analysis method for feature extraction in hyperspectral remote sensing imagery, with improved performance in both ill-posed and poor-posed conditions. The proposed method combines unsupervised methods (local linear feature extraction methods and supervised method (linear discriminant analysis) in a novel framework without any free parameters. The underlying idea is to design an optimal projection matrix, which preserves the local neighborhood information inferred from unlabeled samples, while simultaneously maximizing the class discrimination of the data inferred from the labeled samples. Experimental results on four real hyperspectral images demonstrate that the proposed method compares favorably with conventional feature extraction methods. Numéro de notice : A2013-013 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2200106 Date de publication en ligne : 28/06/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2200106 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32151
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 1 Tome 1 (January 2013) . - pp 184 - 198[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2013011A RAB Revue Centre de documentation En réserve L003 Disponible Super-resolution image analysis as a means of monitoring bracken (Pteridium aquilinum) distributions / Jennie Holland in ISPRS Journal of photogrammetry and remote sensing, vol 75 (January 2013)PermalinkUpdating land-cover maps by classification of image time series : A novel change-detection-driven transfer learning approach / Begüm Demir in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)PermalinkVery high resolution urban land cover extraction using airborne hyperspectral images / Arnaud Le Bris (April 2013)PermalinkAbsolute radiometric calibration of Earth radiation measurement on FY-3B and its comparison with CERES-Aqua data / H. Qiu in IEEE Transactions on geoscience and remote sensing, vol 50 n° 12 (December 2012)PermalinkAutomatic co-registration of satellite time series / M. Gianinetto in Photogrammetric record, vol 27 n° 140 (December 2012 - February 2013)PermalinkCross-calibration of the total ozone unit (TOU) with the ozone monitoring instrument (OMI) and SBUV/2 for environmental applications / W. Wang in IEEE Transactions on geoscience and remote sensing, vol 50 n° 12 (December 2012)PermalinkImage matching of satellite data based on quadrilateral control networks / A. Sedaghat in Photogrammetric record, vol 27 n° 140 (December 2012 - February 2013)PermalinkTélédétection de la trame verte arborée en haute résolution par morphologie mathématique / E. Maire in Revue internationale de géomatique, vol 22 n° 4 (décembre 2012 – février 2013)PermalinkAerial image mosaicking with aid of vector roads / D. Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 11 (November 2012)PermalinkEdge-guided multiscale segmentation of satellite multispectral imagery / J. Chen in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)PermalinkIntegrating Landsat-7 imagery with physics-based models for quantitative mapping of coastal waters near river discharges / Nima Pahlevan in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 11 (November 2012)PermalinkMapping nighttime flood from MODIS observations using support vector machines / R. Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 11 (November 2012)PermalinkMatching of straight line segments from aerial stereo images of urban areas / A. Ok in ISPRS Journal of photogrammetry and remote sensing, vol 74 (Novembrer 2012)PermalinkTotal variation spatial regularization for sparse hyperspectral unmixing / M. Iordache in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)PermalinkTriangular factorization-based simplex algorithms for hyperspectral unmixing / W. Xia in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)PermalinkA vector sift detector for interest point detection in hyperspectral imagery / L. Dorado-Munoz in IEEE Transactions on geoscience and remote sensing, vol 50 n° 11 Tome 1 (November 2012)PermalinkAn automated system for image-to-vector georeferencing / Y. Li in Cartography and Geographic Information Science, vol 39 n° 4 (October 2012)PermalinkDimensionality reduction of hyperspectral data using spectral fractal feature / K. Mukherjee in Geocarto international, vol 27 n° 6 (October 2012)PermalinkHyperspectral image denoising employing a spectral-spatial adaptive total variation model / Q. Yuan in IEEE Transactions on geoscience and remote sensing, vol 50 n° 10 Tome 1 (October 2012)PermalinkSemisupervised classification of remote sensing images with active queries / Jordi Munoz-Mari in IEEE Transactions on geoscience and remote sensing, vol 50 n° 10 Tome 1 (October 2012)PermalinkA supervised and fuzzy-based approach determine optimal multi-resolution image segmentation parameters / H. Tong in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 10 (October 2012)PermalinkA complete processing chain for shadow detection and reconstruction in VHR images / L. Lorenzi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)PermalinkIncreasing robustness of postclassification change detection using time series of land cover maps / Pieter Kempeneers in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)PermalinkInformation fusion in the redundant-wavelet-transform domain for noise-robust hyperspectral classification / S. Prasad in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)PermalinkMultiple endmember unmixing of CHRIS/Proba imagery for mapping impervious surfaces in urban and suburban environments / Luca Demarchi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)PermalinkTopographic corrections of satellite data for regional monitoring / S. Goslee in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 9 (September 2012)PermalinkA variational gradient-based fusion method for visible and SWIR imagery / H. Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 9 (September 2012)PermalinkApplying six classifiers to airborne hyperspectral imagery for detecting giant reed / C. Yang in Geocarto international, vol 27 n° 5 (August 2012)PermalinkAutomatic detection and segmentation of orchards using very high resolution imagery / Selim Aksoy in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)PermalinkClassification of urban tree species using hyperspectral imagery / R. Jensen in Geocarto international, vol 27 n° 5 (August 2012)PermalinkEvaluating classification techniques for mapping vertical geology using field-based hyperspectral sensors / R.J. Murphy in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)PermalinkFusion of feature selection and optimized immune networks for hyperspectral image classification of urban landscapes / J. Im in Geocarto international, vol 27 n° 5 (August 2012)PermalinkHyperspectral band clustering and band selection for urban land cover classification / H. Su in Geocarto international, vol 27 n° 5 (August 2012)PermalinkLocal coregistration adjustment for anomalous change detection / J. Theiler in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)PermalinkMapping impervious surfaces from superresolution enhanced CHRIS/Proba imagery using multiple endmember unmixing / Luca Demarchi in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)PermalinkMemory-based cluster sampling for remote sensing image classification / Michele Volpi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)PermalinkSatellite image time series analysis under time warping / F. Petitjean in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)PermalinkSpatio-temporal MODIS EVI gap filling under cloud cover: An example in Scotland / L. Poggio in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)PermalinkSynthesizing urban remote sensing through application, scale, data and case studies / E.A. Wentz in Geocarto international, vol 27 n° 5 (August 2012)PermalinkTemporal mixture analysis for estimating impervious surface area from multi-temporal MODIS NDVI data in Japan / F. Yang in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)PermalinkDetecting and correcting motion blur from images shot with channel-dependent exposure time / Lâmân Lelégard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)PermalinkExtraction of vineyards out of aerial photo-image using texture information / Arnaud Le Bris in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)PermalinkStreamed vertical rectangle detection in terrestrial laser scans for facade database / Jérôme Demantké in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)PermalinkAn automated approach for updating land cover maps based on integrated change detection and classification methods / X. Chen in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)PermalinkApplication of time series Landsat images to examining land-use / land-cover dynamic change / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 7 (July 2012)Permalink