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Manual of photogrammetry, sixth edition / J. Chris Mcglone (2013)
Titre : Manual of photogrammetry, sixth edition Type de document : Guide/Manuel Auteurs : J. Chris Mcglone, Éditeur scientifique ; George Y.G. Lee, Éditeur scientifique Mention d'édition : sixth edition Editeur : Bethesda [Maryland - Etats-Unis] : American Society for Photogrammetry and Remote Sensing ASPRS Année de publication : 2013 Importance : 1318 p. Format : 18 x 26 cm ISBN/ISSN/EAN : 978-1-57083-099-0 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie
[Termes IGN] algèbre linéaire
[Termes IGN] analyse en composantes principales
[Termes IGN] analyse texturale
[Termes IGN] appariement d'images
[Termes IGN] archéologie aérienne
[Termes IGN] caméra numérique
[Termes IGN] capteur actif
[Termes IGN] capteur imageur
[Termes IGN] capteur optique
[Termes IGN] compression d'image
[Termes IGN] erreur systématique
[Termes IGN] estimation statistique
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] extraction automatique
[Termes IGN] filtrage numérique d'image
[Termes IGN] fonction de transfert de modulation
[Termes IGN] géométrie projective
[Termes IGN] histoire des sciences et techniques
[Termes IGN] instrument d'optique
[Termes IGN] instrument de photogrammétrie
[Termes IGN] matrice
[Termes IGN] modèle numérique de surface
[Termes IGN] modélisation géométrique de prise de vue
[Termes IGN] modélisation radiométrique de prise de vue
[Termes IGN] morphologie mathématique
[Termes IGN] photogrammétrie
[Termes IGN] photogrammétrie analytique
[Termes IGN] photogrammétrie architecturale
[Termes IGN] photogrammétrie métrologique
[Termes IGN] photogrammétrie numérique
[Termes IGN] radar imageur
[Termes IGN] radiomètre
[Termes IGN] réalité virtuelle
[Termes IGN] reconstruction 3D
[Termes IGN] rééchantillonnage
[Termes IGN] restauration d'image
[Termes IGN] station de travail de photogrammétrie numérique
[Termes IGN] système de coordonnées
[Termes IGN] système de numérisation mobile
[Termes IGN] traitement d'image
[Termes IGN] transformation géométriqueIndex. décimale : 33.00 Photogrammétrie - généralités Résumé : (Editeur) Under the leadership of J. Chris McGlone, PhD, CP, as Editor-in-Chief and George Y.G. Lee, PhD, Technical Editor, the Manual covers photogrammetry in depth, as well as its constituent technologies, providing the student, practitioner, or researcher with a single valuable reference resource. The topics addressed within the Manual include: • Mathematics: the perspective geometry which underlies the imaging process and its current usage in computer vision, the statistical modeling of measurement error, and the basic photogrammetric operations of resection, intersection, and triangulation, coordinate transformation • Image acquisition: the physics of optical systems and imaging chips, digital airborne and satellite sensors • Digital photogrammetry: image processing, computer vision, and their applications in photogrammetry • Photogrammetric operations: flight planning and GPS/INS utilization • Photogrammetric products: standard product types and formats and their associated accuracy standards • Current applications: mobile mapping vans, close-range industrial photogrammetry, space measurements, and forensic photogrammetry • Bibliography: each chapter has an extensive bibliography to guide further study. These topics are covered by contributing authors who combine years of experience with many aspects of photogrammetry and familiarity with the state-of-the-art; many of the authors have been pivotal in defining the current state-of-the-art of digital photogrammetry. Note de contenu : 1 A brief history of photogrametry
2 Mathematical concepts in photogrammetry
3 The mathematics of photogrammetry
4 Elements of photogrammetrics optics
5 Digital image processing
6 Basic computer vision techniques
7 Detectors and sensors
8 Cameras and sensing sytems
9 Photogrammetric platforms
10 Analytical photogrammetric operations
11 Measurement and automation practices in photogrammetry
12 Photogrammetric products
13 Photogrammetric applications
14 photogrammetric project and mission planning
Index
Color platesNuméro de notice : 15733 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Manuel de cours Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=40738 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 15733-02 33.00 Livre Centre de documentation Photogrammétrie - Lasergrammétrie Disponible 15733-01 33.00 Livre Centre de documentation Photogrammétrie - Lasergrammétrie Disponible 15733-03 DEP-EXM Livre LASTIG Dépôt en unité Exclu du prêt 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)
[article]
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]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013011B 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)
[article]
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]Réservation
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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]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013011A RAB Revue Centre de documentation En réserve L003 Disponible Tree species discrimination in tropical forests using airborne imaging spectroscopy / Jean-Baptiste Féret in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)
[article]
Titre : Tree species discrimination in tropical forests using airborne imaging spectroscopy Type de document : Article/Communication Auteurs : Jean-Baptiste Féret, Auteur ; Gregory P. Asner, Auteur Année de publication : 2013 Article en page(s) : pp 73 - 84 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse discriminante
[Termes IGN] arbre (flore)
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] distance de Bhattacharyya
[Termes IGN] espèce végétale
[Termes IGN] forêt tropicale
[Termes IGN] Hawaii (Etats-Unis)
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] segmentation
[Termes IGN] spectroscopieRésumé : (Auteur) We identify canopy species in a Hawaiian tropical forest using supervised classification applied to airborne hyperspectral imagery acquired with the Carnegie Airborne Observatory-Alpha system. Nonparametric methods (linear and radial basis function support vector machine, artificial neural network, and k-nearest neighbor) and parametric methods (linear, quadratic, and regularized discriminant analysis) are compared for a range of species richness values and training sample sizes. We find a clear advantage in using regularized discriminant analysis, linear discriminant analysis, and support vector machines. No unique optimal classifier was found for all conditions tested, but we highlight the possibility of improving support vector machine classification with a better optimization of its free parameters. We also confirm that a combination of spectral and spatial information increases accuracy of species classification: we combine segmentation and species classification from regularized discriminant analysis to produce a map of the 17 discriminated species. Finally, we compare different methods to assess spectral separability and find a better ability of Bhattacharyya distance to assess separability within and among species. The results indicate that species mapping is tractable in tropical forests when using high-fidelity imaging spectroscopy. Numéro de notice : A2013-010 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2199323 Date de publication en ligne : 16/07/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2199323 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32148
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 1 Tome 1 (January 2013) . - pp 73 - 84[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013011A RAB Revue Centre de documentation En réserve L003 Disponible Apports des données ALOS PALSAR polarimétriques à la détection des zones humides littorales (Sassandra, Côte d'Ivoire) / Kouakou Hervé Kouassi in Photo interprétation, European journal of applied remote sensing, vol 48 n° 4 (décembre 2012)PermalinkContribution des images ASTER à la connaissance des aquifères fracturés de la région de Duékoué (Ouest de la Côte d'Ivoire) / Aimé Koudou in Photo interprétation, European journal of applied remote sensing, vol 48 n° 4 (décembre 2012)PermalinkPhytosociological characterization of the Juniperus phoenicea L. subsp. turbinata (Guss.) Nyman formations in the Italo-Tyrrhenian Province (Mediterranean Region) / Lorenzo Gianguzzi in Plant sociology, vol 49 n° 2 (December 2012)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)PermalinkBuilt-up and vegetation extraction and density mapping using WorldView-II / A. Kumar in Geocarto international, vol 27 n° 7 (November 2012)PermalinkMapping malaria severity zones with Nigeriasat-1 incorporated into geographical information system / E. Ogunbadewa in Geocarto international, vol 27 n° 7 (November 2012)PermalinkCluster recognition in spatial-temporal sequences: the case of forest fires / C. Vega Orozco in Geoinformatica, vol 15 n° 4 (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)PermalinkEntrepôts de données spatiales et territoires : pour qui, pour quoi faire ? / Nathalie Dejour in Géomatique expert, n° 88 (01/09/2012)PermalinkUtilisation de la télédétection et de données socio-économiques et écologiques pour comprendre l'impact des dynamiques de l'occupation des sols à Pacaja (Brésil) / J. Oszwald in Revue Française de Photogrammétrie et de Télédétection, n° 198 - 199 (Septembre 2012)PermalinkClassification of urban tree species using hyperspectral imagery / R. Jensen 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)PermalinkIconMap-based visualisation technique and its application in soil fertility analysis / X. Zhang in Cartographic journal (the), vol 49 n° 3 (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)PermalinkTrees detection from laser point clouds acquired in dense urban areas by a mobile mapping system / Fabrice Monnier in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)PermalinkSeparation of global time-variable gravity signals into maximally independent components / E. Forootan in Journal of geodesy, vol 86 n° 7 (July 2012)PermalinkDiscovering spatial patterns in origin-destination mobility data / D. Guo in Transactions in GIS, vol 16 n° 3 (June 2012)PermalinkEfficient parallel algorithm for pixel classification in remote sensing imagery / U. Maulik in Geoinformatica, vol 16 n° 2 (April 2012)PermalinkFuzzy analysis for modeling regional delineation and development: The case of the Sardinian mining geopark / G. Manca in Transactions in GIS, vol 16 n° 1 (February 2012)PermalinkPermalinkCartographie du déboisement à partir de données à haute résolution spatiale / Yannick Philippets (2012)PermalinkDétection et identification de zones de végétation arborée: utilisation conjointe d'images satellite RapidEye et de données BDOrtho / François Tassin (2012)PermalinkJoint processing of Landsat and ALOS-PALSAR data for forest mapping and monitoring / E. Lehmann in IEEE Transactions on geoscience and remote sensing, vol 50 n° 1 (January 2012)PermalinkTraitements numériques des images de télédétection, Vol. 3. Traitements appliqués à la photo-interprétation / Olivier de Joinville (2012)PermalinkPermalinkClustering of detected changes in high-resolution satellite imagery using a stabilized competitive agglomeration algorithm / O. 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Khelifa in Bulletin des sciences géographiques, n° 26 (octobre 2011)PermalinkEmpirical comparison of full-waveform Lidar algorithms: range extraction and discrimination performance / C. Parrish in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 8 (August 2011)PermalinkApproche géosémantique intégrée pour les cubes évolutifs de données géospatiales / Mohamed Bakillah in Revue internationale de géomatique, vol 21 n° 1 (mars – mai 2011)PermalinkElectromagnetic land surface classification through integration of optical and radar remote sensing data / J. Baek in IEEE Transactions on geoscience and remote sensing, vol 49 n° 4 (April 2011)PermalinkAnalyse spatiale de l'information géographique / R. Caloz (2011)PermalinkComputational method for the point cluster analysis on networks / K. 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