Descripteur
Termes IGN > imagerie > image numérique
image numériqueSynonyme(s)image en mode mailléVoir aussi |
Documents disponibles dans cette catégorie (2388)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping / Luca Demarchi in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
[article]
Titre : Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping Type de document : Article/Communication Auteurs : Luca Demarchi, Auteur ; Frank Canters, Auteur ; Claude Cariou, Auteur ; Giorgio Licciardi, Auteur ; Jonathan Cheung-Wai Chan, Auteur Année de publication : 2014 Article en page(s) : pp 166 - 179 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Airborne Prism Experiment
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image APEX
[Termes IGN] image hyperspectrale
[Termes IGN] Perceptron multicoucheRésumé : (Auteur) Despite the high richness of information content provided by airborne hyperspectral data, detailed urban land-cover mapping is still a challenging task. An important topic in hyperspectral remote sensing is the issue of high dimensionality, which is commonly addressed by dimensionality reduction techniques. While many studies focus on methodological developments in data reduction, less attention is paid to the assessment of the proposed methods in detailed urban hyperspectral land-cover mapping, using state-of-the-art image classification approaches. In this study we evaluate the potential of two unsupervised data reduction techniques, the Autoassociative Neural Network (AANN) and the BandClust method – the first a transformation based approach, the second a feature-selection based approach – for mapping of urban land cover at a high level of thematic detail, using an APEX 288-band hyperspectral dataset. Both methods were tested in combination with four state-of-the-art machine learning classifiers: Random Forest (RF), AdaBoost (ADB), the multiple layer perceptron (MLP), and support vector machines (SVM). When used in combination with a strong learner (MLP, SVM) BandClust produces classification accuracies similar to or higher than obtained with the full dataset, demonstrating the method’s capability of preserving critical spectral information, required for the classifier to successfully distinguish between the 22 urban land-cover classes defined in this study. In the AANN data reduction process, on the other hand, important spectral information seems to be compromised or lost, resulting in lower accuracies for three of the four classifiers tested. Detailed analysis of accuracies at class level confirms the superiority of the SVM/Bandclust combination for accurate urban land-cover mapping using a reduced hyperspectral dataset. This study also demonstrates the potential of the new APEX sensor data for detailed mapping of land cover in spatially and spectrally complex urban areas. Numéro de notice : A2014-018 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32923
in ISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 166 - 179[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2014011 RAB Revue Centre de documentation En réserve L003 Disponible Assessment of the image misregistration effects on object-based change detection / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
[article]
Titre : Assessment of the image misregistration effects on object-based change detection Type de document : Article/Communication Auteurs : Gang Chen, Auteur ; Kaiguang Zhao, Auteur ; Ryan Powers, Auteur Année de publication : 2014 Article en page(s) : pp 19 - 27 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] classification orientée objet
[Termes IGN] détection de changement
[Termes IGN] estimation de précision
[Termes IGN] image multitemporelle
[Termes IGN] image SPOT 5Résumé : (Auteur) High-spatial resolution remote sensing imagery provides unique opportunities for detailed characterization and monitoring of landscape dynamics. To better handle such data sets, change detection using the object-based paradigm, i.e., object-based change detection (OBCD), have demonstrated improved performances over the classic pixel-based paradigm. However, image registration remains a critical pre-process, with new challenges arising, because objects in OBCD are of various sizes and shapes. In this study, we quantified the effects of misregistration on OBCD using high-spatial resolution SPOT 5 imagery (5 m) for three types of landscapes dominated by urban, suburban and rural features, representing diverse geographic objects. The experiments were conducted in four steps: (i) Images were purposely shifted to simulate the misregistration effect. (ii) Image differencing change detection was employed to generate difference images with all the image-objects projected to a feature space consisting of both spectral and texture variables. (iii) The changes were extracted using the Mahalanobis distance and a change ratio. (iv) The results were compared to the ‘real’ changes from the image pairs that contained no purposely introduced registration error. A pixel-based change detection method using similar steps was also developed for comparisons. Results indicate that misregistration had a relatively low impact on object size and shape for most areas. When the landscape is comprised of small mean object sizes (e.g., in urban and suburban areas), the mean size of ‘change’ objects was smaller than the mean of all objects and their size discrepancy became larger with the decrease in object size. Compared to the results using the pixel-based paradigm, OBCD was less sensitive to the misregistration effect, and the sensitivity further decreased with an increase in local mean object size. However, high-spatial resolution images typically have higher spectral variability within neighboring pixels than the relatively low resolution datasets. As a result, accurate image registration remains crucial to change detection even if an object-based approach is used. Numéro de notice : A2014-008 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32913
in ISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 19 - 27[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2014011 RAB Revue Centre de documentation En réserve L003 Disponible Caractérisation et cartographie de la structure forestière à partir d'images satellitaires à très haute résolution spatiale / Benoit Beguet (2014)
Titre : Caractérisation et cartographie de la structure forestière à partir d'images satellitaires à très haute résolution spatiale Type de document : Thèse/HDR Auteurs : Benoit Beguet, Auteur Editeur : Talence : Université de Bordeaux 3 Michel de Montaigne Année de publication : 2014 Format : 21 x 30 cm Note générale : bibliographie
Sciences de la Terre, Université Michel de Montaigne - Bordeaux IIILangues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse texturale
[Termes IGN] caractérisation
[Termes IGN] carte forestière
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité de la végétation
[Termes IGN] forêt tempérée
[Termes IGN] hauteur des arbres
[Termes IGN] image multibande
[Termes IGN] image panchromatique
[Termes IGN] image Pléiades-HR
[Termes IGN] image Quickbird
[Termes IGN] Landes (40)
[Termes IGN] Pinus pinaster
[Termes IGN] régression multiple
[Termes IGN] structure d'un peuplement forestierIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Les images à très haute résolution spatiale (THR) telles que les images Pléiades (50 cm en Panchromatique, 2m en multispectral) rendent possible une description fine de la structure forestière (distribution et dimensions des arbres) à l'échelle du peuplement, en exploitant la relation entre la structure spatiale des arbres et la texture d'image quand la taille du pixel est inférieure à la dimension des arbres. Cette attente répond au besoin d'inventaire spatialisé de la ressource forestière à l'échelle du peuplement et de ses changements dus à la gestion forestière, à l'aménagement du territoire ou aux événements catastrophiques. L'objectif est double: (1) évaluer le potentiel de la texture d'images THR pour estimer les principales variables de structure forestière (diamètre des couronnes, diamètre du tronc, hauteur, densité ou espacement des arbres) à l'échelle du peuplement; (2) sur ces bases, classer les données image, au niveau pixel, par types de structure forestière afin de produire l'information spatialisée la plus fine possible. Les principaux développements portent sur l'automatisation du paramètrage, la sélection de variables, la modélisation par régression multivariable et une approche de classification par classifieurs d'ensemble (Forêts Aléatoires ou Random Forests). Ils sont testés et évalués sur deux sites de la forêt landaise de pin maritime à partir de trois images Pléiades et une Quickbird, acquises dans diverses conditions (saison, position du soleil, angles de visée). La méthodologie proposée est générique. La robustesse aux conditions d'acquisition des images est évaluée. Les résultats montrent que des variations fines de texture caractéristiques de celles de la structure forestière sont bien identifiables. Les performances en terme d'estimation des variables forestières (RMSE) : ~1.1 m pour le diamètre des couronnes, ~3 m pour la hauteur des arbres ou encore ~0.9 m pour leur espacement, ainsi qu'en cartographie des structures forestières (~82 % de taux de bonne classification pour la reconnaissance des 5 classes principales de la structure forestière) sont satisfaisantes d'un point de vue opérationnel. L'application à des images multi-annuelles permettra d'évaluer leur capacité à détecter et cartographier des changements tels que coupe forestière, mitage urbain ou encore dégâts de tempête. Numéro de notice : 17119 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse française Note de thèse : thèse de doctorat : Sciences de la Terre : Bordeaux 3 : 2014 Organisme de stage : Géoressources et Environnement nature-HAL : Thèse DOI : sans En ligne : https://hal.science/tel-02800745v1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80289 Collaborative sparse regression for hyperspectral unmixing / Marian-Daniel Iordache in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)
[article]
Titre : Collaborative sparse regression for hyperspectral unmixing Type de document : Article/Communication Auteurs : Marian-Daniel Iordache, Auteur ; José Bioucas-Dias, Auteur ; Antonio J. Plaza, Auteur Année de publication : 2014 Article en page(s) : pp 341 - 354 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] accentuation d'image
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] image hyperspectrale
[Termes IGN] régressionRésumé : (Auteur) Sparse unmixing has been recently introduced in hyperspectral imaging as a framework to characterize mixed pixels. It assumes that the observed image signatures can be expressed in the form of linear combinations of a number of pure spectral signatures known in advance (e.g., spectra collected on the ground by a field spectroradiometer). Unmixing then amounts to finding the optimal subset of signatures in a (potentially very large) spectral library that can best model each mixed pixel in the scene. In this paper, we present a refinement of the sparse unmixing methodology recently introduced which exploits the usual very low number of endmembers present in real images, out of a very large library. Specifically, we adopt the collaborative (also called “multitask” or “simultaneous”) sparse regression framework that improves the unmixing results by solving a joint sparse regression problem, where the sparsity is simultaneously imposed to all pixels in the data set. Our experimental results with both synthetic and real hyperspectral data sets show clearly the advantages obtained using the new joint sparse regression strategy, compared with the pixelwise independent approach. Numéro de notice : A2014-038 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2240001 En ligne : https://doi.org/10.1109/TGRS.2013.2240001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32943
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 1 tome 1 (January 2014) . - pp 341 - 354[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2014011A RAB Revue Centre de documentation En réserve L003 Disponible Combining top-down and bottom-up approaches for building detection in a single very high resolution satellite image / Mahmoud Mohammed Sidi Youssef (2014)
Titre : Combining top-down and bottom-up approaches for building detection in a single very high resolution satellite image Type de document : Article/Communication Auteurs : Mahmoud Mohammed Sidi Youssef, Auteur ; Clément Mallet , Auteur ; Nesrine Chehata , Auteur ; Arnaud Le Bris , Auteur ; Adrien Gressin , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Conférence : IGARSS 2014, International Geoscience And Remote Sensing Symposium 13/07/2014 18/07/2014 Québec Québec - Canada Proceedings IEEE Importance : pp 4820 - 4823 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification
[Termes IGN] détection du bâti
[Termes IGN] image multibande
[Termes IGN] image Pléiades-HR
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] reconnaissance de formesRésumé : (auteur) Building detection from geospatial optical images has been a popular topic of research for the last twenty years and in particular with the emergence of very high resolution satellites. Existing methods exhibit various flaws and prevent them from being efficient at large scales of space and time: they are context-dependent, require a tedious parameter tuning or several data sources. In this paper, we propose a fully automatic method that alleviates some of these issues by combining the strengths of bottom-up and top-down approaches, i.e., of both classification and pattern recognition algorithms. This allows to correctly detect the objects by geometric prior knowledge while finely delineating their borders and preserving their shapes. The method is evaluated over a complex area of more than 230 buildings using a 0.5 m multispectral pansharpened Pleiades image. Numéro de notice : C2014-028 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2014.6947573 Date de publication en ligne : 10/11/2014 En ligne : http://dx.doi.org/10.1109/IGARSS.2014.6947573 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83398 Comparaison de méthodes d'extraction automatique à partir d'images multispectrales / Valerio Baiocchi in Géomatique expert, n° 96 (01/01/2014)PermalinkPermalinkDétection de bâtiments à partir d’une image satellitaire par combinaison d’approches ascendante et descendante / Mohamed Mahmoud Sidi Yousseff (2014)PermalinkPermalinkEvaluation of MODIS data for improved monitoring of the Caspian Sea / Ayoub Moradi in International Journal of Remote Sensing IJRS, vol 35 n° 16 (January 2014)PermalinkGeographic Object-Based Image Analysis: Towards a new paradigm / Thomas Blaschke in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkHierarchical extraction of landslides from multiresolution remotely sensed optical images / Camille Kurtz in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)PermalinkHyperspectral image classification using nearest feature line embedding approach / Yang-Lang Chang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)PermalinkImagerie de télédétection / Florence Tupin (2014)PermalinkImagerie terrestre urbaine : vers une méthode physique d'estimation de la réflectance / Fabien Coubard (2014)PermalinkImages virtuelles et horizons du regard / Jean-François Coulais (2014)PermalinkIndividual tree segmentation over large areas using airborne LiDAR point cloud and very high resolution optical imagery / Yuchu Qin (2014)PermalinkA local contrast method for small infrared target detection / C.L. Philip Chen in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 2 (January 2014)PermalinkMapping a priori defined plant associations using remotely sensed vegetation characteristics / Hans D. Rölofsen in Remote sensing of environment, vol 140 (January 2014)PermalinkPatch-based information reconstruction of cloud-contaminated multitemporal images / Chao-Hung Lin in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)PermalinkReconstruction de modèles 3D photoréalistes de façades à partir de données image et laser terrestre / Jérôme Demantké (2014)PermalinkRemote sensing image segmentation by combining spectral and texture features / H. Li in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)PermalinkPermalinkRestoration of information obscured by mountainous shadows through Landsat TM/ETM+ images without the use of DEM data : A new method / Yuan Zhou in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)PermalinkSynergetic use of optical and polSAR imagery for urban impervious surface estimation / Huadong Guo in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 1 (January 2014)PermalinkUse intermediate results of wrapper band selection methods: A first step toward the optimization of spectral configuration for land cover classifications / Arnaud Le Bris (2014)PermalinkAutomated detection of buildings from single VHR multispectral images using shadow information and graph cuts / Ali Ozgun Ok in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)PermalinkGeneration and validation of high-resolution DEMs from Worldview-2 stereo data / Umut Gunes Sefercik in Photogrammetric record, vol 28 n° 144 (December 2013 - February 2014)PermalinkTemperature and emissivity separation from Thermal Airborne Hyperspectral Imager (TASI) data / Yang Hang in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 12 (December 2013)PermalinkThe 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)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)PermalinkModeling of spatio-temporal dynamics of land use and land cover in a part of Brahmaputra River basin using Geoinformatic techniques / M. Sarabuddin Mondal in Geocarto international, vol 28 n° 7-8 (November - December 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)PermalinkChange Detection in 3D Point Clouds Acquired by a Mobile Mapping System / Wen Xiao in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-5 W2 (November 2013)PermalinkA comprehensive review of earthquake-induced building damage detection with remote sensing techniques / Laigen Dong in ISPRS Journal of photogrammetry and remote sensing, vol 84 (October 2013)PermalinkMéthode de sélection des bandes à base de l'analyse en composantes indépendantes appliquée aux images hyperspectrales de télédétection / Seloua Chouaf in Revue Française de Photogrammétrie et de Télédétection, n° 204 (Octobre 2013)PermalinkAssessing the relationship between ground measurements and object-based image analysis of land cover classes in Pinyon and Juniper Woodlands / April Hulet in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 9 (September 2013)PermalinkAutomated detection of slum area change in Hyderabad, India using multitemporal satellite imagery / Oleksandr Kit in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)PermalinkAutomatic extraction of building roofs using LIDAR data and multispectral imagery / Mohammad Awrangjeb in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)PermalinkGeneralized composite kernel framework for hyperspectral image classification / J. Li in IEEE Transactions on geoscience and remote sensing, vol 51 n° 9 (September 2013)PermalinkHyperspectral image noise reduction based on rank-1 tensor decomposition / Xian Guoa in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)PermalinkUsing video acquired from an unmanned aerial vehicle (UAV) to measure fracture orientation in an open-pit mine / Tara McLeod in Geomatica, vol 67 n° 3 (September 2013)PermalinkNon-linear partial least square regression increases the estimation accuracy of grass nitrogen and phosphorus using in situ hyperspectral and environmental data / Abel Ramoelo in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)PermalinkRegistration of optical images with lidar data and its accuracy assessment / Shunyl Zheng in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 8 (August 2013)PermalinkUsing hyperspectral reflectance data to assess biocontrol damage of giant salvinia / James H. Everitt in Geocarto international, vol 28 n° 5-6 (August - October 2013)PermalinkLa combinaison d'indicateurs de changement pour le suivi de l'évolution de l'occupation du sol à partir d'imagerie satellitale / Faten Katlane in Revue Française de Photogrammétrie et de Télédétection, n° 203 (Juillet 2013)PermalinkDeblurring and sparse unmixing for hyperspectral images / Xi-Le Zhao in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 1 (July 2013)PermalinkGraph-regularized low-rank representation for destriping of hyperspectral images / Xiaoqiang Lu in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 1 (July 2013)PermalinkIndependent two-step thresholding of binary images in inter-annual land cover change/no-change identification / Priyakant Sinha in ISPRS Journal of photogrammetry and remote sensing, vol 81 (July 2013)PermalinkSemisupervised self-learning for hyperspectral image classification / Immaculada Dopido in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 1 (July 2013)PermalinkSpectral unmixing in multiple-kernel Hilbert space for hyperspectral imagery / Yanfeng Gu in IEEE Transactions on geoscience and remote sensing, vol 51 n° 7 Tome 1 (July 2013)PermalinkUtility of the wavelet transform for LAI estimation using hyperspectral data / Asim Banskota in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 7 (July 2013)PermalinkBand grouping versus band clustering in SVM ensemble classification of hyperspectral imagery / Behnaz Bigdeli in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 6 (June 2013)PermalinkShadow detection in very high spatial resolution aerial images: A comparative study / Karine R.M. Adeline in ISPRS Journal of photogrammetry and remote sensing, vol 80 (June 2013)PermalinkTexture augmented detection of macrophyte species using decision trees / Cameron Proctor in ISPRS Journal of photogrammetry and remote sensing, vol 80 (June 2013)PermalinkUse of handheld thermal imager data for airborne mapping of fire radiative power and energy and flame front rate of spread / Ronan Paugam in IEEE Transactions on geoscience and remote sensing, vol 51 n° 6 Tome 1 (June 2013)PermalinkUsing reverse viewshed analysis to assess the location correctness of visually generated VGI / Hansi Senaratne in Transactions in GIS, vol 17 n° 3 (June 2013)PermalinkAttraction-repulsion model-based subpixel mapping of multi-/hyperspectral imagery / Xiaohua Tong in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)PermalinkChange detection and deformation analysis in point clouds: Application to rock face monitoring / Marco Scaioni in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 5 (May 2013)PermalinkA classification algorithm for hyperspectral images based on synergetics theory / Daniele Cerra in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)PermalinkCommercial tree species discrimination using airborne AISA Eagle hyperspectral imagery and partial least squares discriminant analysis (PLS-DA) in KwaZulu–Natal, South Africa / Kabir Yunus Peerbhay in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)PermalinkHistogram curve matching approaches for object-based image classification of land cover and land use / Sory I. Toure in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 5 (May 2013)PermalinkManifold regularized sparse NMF for hyperspectral unmixing / Xiaqiang Lu in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)PermalinkModels and methods for automated background density estimation in hyperspectral anomaly detection / Stefania Matteoli in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)PermalinkPiecewise convex multiple-model endmember detection and spectral unmixing / Alina Zare in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)PermalinkRegion-based automatic building and forest change detection on Cartosat-1 stereo imagery / Jing Tian in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)PermalinkA sparse image fusion algorithm with application to pan-sharpening / Xiao Xiang Zhu in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)PermalinkAn experimental comparison of semi-supervised learning algorithms for multispectral image classification / Enmei Tu in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 4 (April 2013)PermalinkDécision cumulative pour la vision dynamique des systèmes / Samia Bouchafa in Revue Française de Photogrammétrie et de Télédétection, n° 202 (Avril 2013)PermalinkDescription de la campagne aéroportée UMBRA : étude de l'impact anthropique sur les écosystèmes urnbains et naturels avec des images THR multispectrales et hyperspectrales / Karine R.M. Adeline in Revue Française de Photogrammétrie et de Télédétection, n° 202 (Avril 2013)PermalinkLow altitude aerial photography applications for digital surface models creation in archaeology / José-Angel Martinez-Del-Pozo in Transactions in GIS, vol 17 n° 2 (April 2013)PermalinkMultiple-spectral-band CRFs for denoising junk bands of hyperspectral imagery / Ping Zhong in IEEE Transactions on geoscience and remote sensing, vol 51 n° 4 Tome 2 (April 2013)PermalinkObject-based fusion of multitemporal multiangle ENVISAT ASAR and HJ-1B multispectral data for urban land-cover mapping / Yifang Ban in IEEE Transactions on geoscience and remote sensing, vol 51 n° 4 Tome 1 (April 2013)PermalinkRational function model in processing historical aerial photographs / Ruijin Ma in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 4 (April 2013)PermalinkSegmentation hyperspectrale de forêts tropicales par arbres de partition binaires / Guillaume Tochon in Revue Française de Photogrammétrie et de Télédétection, n° 202 (Avril 2013)PermalinkSTARS : A new method for multitemporal remote sensing / Marcio Pupin Mello in IEEE Transactions on geoscience and remote sensing, vol 51 n° 4 Tome 1 (April 2013)PermalinkThe emergency social network: Geovisualising Twitter provides early warnings and on-scene reports to first responders and emergency managers / Deborah Davis in GEO: Geoconnexion international, vol 12 n° 4 (april 2013)PermalinkAssessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study / Gyanesh Chander in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 1 (March 2013)PermalinkGSICS inter-calibration of infrared channels of geostationary imagers using Metop-IASI / Tim J. Hewison in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 1 (March 2013)PermalinkLearning with transductive SVM for semisupervised pixel classification of remote sensing imagery / Ujjwal Maulik in ISPRS Journal of photogrammetry and remote sensing, vol 77 (March 2013)PermalinkSampling piecewise convex unmixing and endmember extraction / Alina Zare in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 2 (March 2013)PermalinkTopological gradient connection analysis for feature detection / Chao-Yuan Lo in Photogrammetric record, vol 28 n° 141 (March - May 2013)PermalinkClassification and reconstruction from random projections for hyperspectral imagery / W. Li in IEEE Transactions on geoscience and remote sensing, vol 51 n° 2 (February 2013)PermalinkA graph-based classification method for hyperspectral images / J. Bai in IEEE Transactions on geoscience and remote sensing, vol 51 n° 2 (February 2013)PermalinkRetrieval of effective leaf area index in heterogeneous forests with terrestrial laser scanning / G. Zheng in IEEE Transactions on geoscience and remote sensing, vol 51 n° 2 (February 2013)PermalinkSpectral angle mapper and object-based classification combined with hyperspectral remote sensing imagery for obtaining land use/cover mapping in a Mediterranean region / George P. Petropoulos in Geocarto international, vol 28 n° 1-2 (February - May 2013)PermalinkSpectral material mapping using hyperspectral imagery : a review of spectral matching and library search methods / Sennaraj Vishnu in Geocarto international, vol 28 n° 1-2 (February - May 2013)PermalinkAppariement entre images de point de vue éloignés par utilisation de carte de profondeur / Narut Soontranon (2013)PermalinkComparaison et évaluation de méthodes d'extraction automatique d'objets sur des images optique et radar / Charlotte Benedetto (2013)PermalinkComparison of VHR panchromatic texture features for tillage mapping / Nesrine Chehata (juillet 2013)PermalinkContribution of texture and red-edge band for vegetated areas detection and identification / Arnaud Le Bris (2013)PermalinkCrop yield estimation based on unsupervised linear unmixing of multidate hyperspectral imagery / B. Luo in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)PermalinkEuroSDR project Commission 1, Radiometric aspects of digital photogrammetric images / Eija Honkavaara (2013)PermalinkPermalinkA hybrid multiview stereo algorithm for modeling urban scenes / Florent Lafarge in IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI, vol 35 n° 1 (January 2013)PermalinkMapping the distribution of ferric iron minerals on a vertical mine face using derivative analysis of hyperspectral imagery (430–970 nm) / R. Murphy in ISPRS Journal of photogrammetry and remote sensing, vol 75 (January 2013)PermalinkMaterial reflectance retrieval in urban tree shadows with physics-based empirical atmospheric correction / Karine R.M. Adeline (2013)PermalinkA 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)PermalinkPermalinkPredicting surface fuel models and fuel metrics using Lidar and CIR imagery in a dense, mountainous forest / Marek Jakubowksi in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 1 (January 2013)Permalink