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Local manifold learning-based k-Nearest-Neighbor for hyperspectral image classification / Li Ma in IEEE Transactions on geoscience and remote sensing, vol 48 n° 11 (November 2010)
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Titre : Local manifold learning-based k-Nearest-Neighbor for hyperspectral image classification Type de document : Article/Communication Auteurs : Li Ma, Auteur ; Jing Tian, Auteur Année de publication : 2010 Article en page(s) : pp 1099 - 4109 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] classification barycentrique
[Termes IGN] image AVIRIS
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectraleRésumé : (Auteur) Approaches to combine local manifold learning (LML) and the k -nearest-neighbor (kNN) classifier are investigated for hyperspectral image classification. Based on supervised LML (SLML) and kNN, a new SLML-weighted kNN (SLML-W kNN) classifier is proposed. This method is appealing as it does not require dimensionality reduction and only depends on the weights provided by the kernel function of the specific ML method. Performance of the proposed classifier is compared to that of unsupervised LML (ULML) and SLML for dimensionality reduction in conjunction with the kNN (ULML- kNN and SLML-k NN). Three LML methods, locally linear embedding (LLE), local tangent space alignment (LTSA), and Laplacian eigenmaps, are investigated with these classifiers. In experiments with Hyperion and AVIRIS hyperspectral data, the proposed SLML-WkNN performed better than ULML- kNN and SLML-k NN, and the highest accuracies were obtained using weights provided by supervised LTSA and LLE. Numéro de notice : A2010-479 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2010.2055876 Date de publication en ligne : 23/08/2010 En ligne : https://doi.org/10.1109/TGRS.2010.2055876 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30672
in IEEE Transactions on geoscience and remote sensing > vol 48 n° 11 (November 2010) . - pp 1099 - 4109[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2010111 RAB Revue Centre de documentation En réserve L003 Disponible Multiple Spectral–Spatial Classification Approach for Hyperspectral Data / Yuliya Tarabalka in IEEE Transactions on geoscience and remote sensing, vol 48 n° 11 (November 2010)
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Titre : Multiple Spectral–Spatial Classification Approach for Hyperspectral Data Type de document : Article/Communication Auteurs : Yuliya Tarabalka, Auteur ; Jon Atli Benediktsson, Auteur ; Jocelyn Chanussot, Auteur ; James C. Tilton, Auteur Année de publication : 2010 Article en page(s) : pp 4122 - 4132 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification multibande
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] segmentation d'imageRésumé : (Auteur) A new multiple-classifier approach for spectral-spatial classification of hyperspectral images is proposed. Several classifiers are used independently to classify an image. For every pixel, if all the classifiers have assigned this pixel to the same class, the pixel is kept as a marker, i.e., a seed of the spatial region with a corresponding class label. We propose to use spectral-spatial classifiers at the preliminary step of the marker-selection procedure, each of them combining the results of a pixelwise classification and a segmentation map. Different segmentation methods based on dissimilar principles lead to different classification results. Furthermore, a minimum spanning forest is built, where each tree is rooted on a classification-driven marker and forms a region in the spectral-spatial classification map. Experimental results are presented for two hyperspectral airborne images. The proposed method significantly improves classification accuracies when compared with previously proposed classification techniques. Numéro de notice : A2010-480 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2010.2062526 Date de publication en ligne : 13/09/2010 En ligne : https://doi.org/10.1109/TGRS.2010.2062526 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30673
in IEEE Transactions on geoscience and remote sensing > vol 48 n° 11 (November 2010) . - pp 4122 - 4132[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2010111 RAB Revue Centre de documentation En réserve L003 Disponible Noise-signal index threshold: a new noise-reduction technique for generation of reference spectra and efficient hyperspectral image classification / K. Kusuma in Geocarto international, vol 25 n° 7 (November 2010)
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Titre : Noise-signal index threshold: a new noise-reduction technique for generation of reference spectra and efficient hyperspectral image classification Type de document : Article/Communication Auteurs : K. Kusuma, Auteur ; D. Ramakrishnan, Auteur ; H. Pandalai, Auteur ; G. Kailash, Auteur Année de publication : 2010 Article en page(s) : pp 569 - 580 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] bruit blanc
[Termes IGN] classification spectrale
[Termes IGN] correction radiométrique
[Termes IGN] filtrage du bruit
[Termes IGN] modèle empirique
[Termes IGN] réponse spectrale
[Termes IGN] seuillage d'imageRésumé : (Auteur) Reference spectra of terrestrial targets are usually collected using field spectro-radiometers for mineral abundance mapping and target detection. These spectra often have noise that masks characteristic absorption and reflection features and affects the efficiency of material mapping. This work aims at obtaining an empirical technique for reduction of high-frequency noise from field spectra. The proposed noise correction technique uses a 'normalized' measure Rn, where Rn = (Ln - Fn)/Ln for each band (n) calculated from field and laboratory spectra of test material, with Fn and Ln being the depth of the absorption feature in field and laboratory spectra, respectively. On the basis of the assumption of the constancy of this ratio in neighbouring bands, an empirical algorithm that approximates the ratio Rn of a noisy band to the corrected ratio of an adjacent band is used to obtain the noise-corrected field spectra. The classification accuracy increases significantly when noise reduced field spectra are used as reference spectra. Numéro de notice : A2010-471 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2010.510582 Date de publication en ligne : 16/09/2010 En ligne : https://doi.org/10.1080/10106049.2010.510582 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30664
in Geocarto international > vol 25 n° 7 (November 2010) . - pp 569 - 580[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2010071 RAB Revue Centre de documentation En réserve L003 Disponible Assessing the quality of geoscientific simulation models with visual analytics methods: a design study / D. Dransch in International journal of geographical information science IJGIS, vol 24 n° 10 (october 2010)
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Titre : Assessing the quality of geoscientific simulation models with visual analytics methods: a design study Type de document : Article/Communication Auteurs : D. Dransch, Auteur ; P. Köthur, Auteur ; S. Schulte, Auteur ; V. Klemann, Auteur ; H. Dobslaw, Auteur Année de publication : 2010 Article en page(s) : pp 1459 - 1479 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de données
[Termes IGN] analyse visuelle
[Termes IGN] données hétérogènes
[Termes IGN] modèle de simulationRésumé : (Auteur) Simulation models are essential means of scientific knowledge building and also the basis for decision-making. Because of their relevance, they have to be assessed thoroughly with respect to their quality. Simulation model assessment comprises two challenges: (a) modelers have to create a comprehensive mental image of the model's quality despite the massive multidimensional, multivariate, and often heterogeneous data; and (b) the model assessment process should be as efficient as possible. We face these challenges with a visual analytics approach. We aim at developing interactive visual representations which, in combination with present computational analysis methods, support the scientist's reasoning process to enhance the assessment of simulation models. In a design study, we analyzed two exemplary reasoning processes which cover the main model assessment procedures: the evaluation of the internal coherence of the model's structure and behavior and the assessment of its empirical validity. The analysis was conducted by means of a user- and task-centered approach which combines several knowledge elicitation techniques and task analysis concepts. We derived domain tasks as well as cognitive actions and developed and implemented interactive visualization components which supplement the statistical analysis methods already used. An informal qualitative user study shows that our visual analytics approach and tools help gain a more detailed mental image and hence a better understanding of the data and the underlying simulation model and allow for a faster and more comprehensive assessment of the simulation model. Numéro de notice : A2010-461 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658816.2010.510800 En ligne : https://doi.org/10.1080/13658816.2010.510800 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30654
in International journal of geographical information science IJGIS > vol 24 n° 10 (october 2010) . - pp 1459 - 1479[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2010061 RAB Revue Centre de documentation En réserve L003 Disponible 079-2010062 RAB Revue Centre de documentation En réserve L003 Disponible Effect of SRTM resolution on morphometric feature identification using neural network - self organizing map / A. Ehsani in Geoinformatica, vol 14 n° 4 (October 2010)
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Titre : Effect of SRTM resolution on morphometric feature identification using neural network - self organizing map Type de document : Article/Communication Auteurs : A. Ehsani, Auteur ; F. Quiel, Auteur ; A. Malekian, Auteur Année de publication : 2010 Article en page(s) : pp 405 - 424 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aire protégée
[Termes IGN] Carpates
[Termes IGN] carte de Kohonen
[Termes IGN] classification par réseau neuronal
[Termes IGN] détection de changement
[Termes IGN] données topographiques
[Termes IGN] géomorphométrie
[Termes IGN] image SIR-C-X-SAR
[Termes IGN] MNS SRTMRésumé : (Auteur) In this study, we present a semi-automatic procedure using Neural Networks—Self Organizing Map—and Shuttle Radar Topography Mission DEMs to characterize morphometric features of the landscape in the Man and Biosphere Reserve “Eastern Carpathians”. We investigate specially the effect of two resolutions, SIR-C with 3 arc seconds and X-SAR with 1 arc second for morphometric feature identification. Specifically we investigate how the SRTM/C band data with 30 m interpolated grid, corresponding to SRTM/X band 30 m, affect the morphometric characterization and topography derivatives. To reduce misregistration between the DEMs, spatial co-registration was performed and a RMSE of 0.48 pixel was achieved. Morphometric parameters such as slope, maximum curvature, minimum curvature and cross-sectional curvature are derived using a bivariate quadratic approximation on 90 m, 30 m and interpolated 30 m DEMs. Self Organizing Map (SOM) is used for the classification of morphometric parameters into ten exclusive and exhaustive classes. These classes were analyzed as morphometric features such as ridge, channel, crest line and planar for all data sets based on feature space (scatter plot), morphometric signatures and 3D inspection of the area. The map quality is analyzed by oblique views with contour lines overlaid. Using the X band DEM with 30 m grid as benchmark, a change detection technique was used to quantify differences in morphometric features and to assess the scale effect going from a 90 m (C-band) DEM to an interpolated 30 m DEM. The same procedure is used to study the effect of different resolutions on morphometric features. Morphometric parameters were computed by a moving window size 5 x 5 (corresponding to 450 m on the ground) over SRTM- 90 m. To cover the same ground area, a moving window size of 15 x 15 is used for the 30 m DEM. The change analysis showed the amount of resolution dependency of morphometric features. Overall, the results showed that the introduced method is very useful for identification of morphometric features based on SRTM resolution. Decreasing the grid size from 90 m to 30 m reveals considerably more detailed information emphasizing local conditions. Comparison between results from DEM-30 m as reference data set and interpolated 30 m, showed a rate of change of 31.5% which is negligible. About 17% of this rate correspond to classes with mean slope > 10°. Of the morphometric parameters, the cross sectional curvature is most sensitive to DEM resolution. Increasing spatial resolution reduces the main constrains for morphometric analysis with SRTM 90 m data, such as unrealistic features and isolated single elements in the output map. So in case of lack of high resolution data, the SRTM 90 m data could be interpolated and used for further geomorphic analysis. Copyright Springer Numéro de notice : A2010-302 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s10707-009-0085-4 Date de publication en ligne : 29/04/2009 En ligne : https://doi.org/10.1007/s10707-009-0085-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30496
in Geoinformatica > vol 14 n° 4 (October 2010) . - pp 405 - 424[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 057-2010041 RAB Revue Centre de documentation En réserve L003 Disponible Géodécisionnel : y'en a pour tous les goûts / Françoise de Blomac in SIG la lettre, n° 120 (octobre 2010)
PermalinkSimilarity weighted instance-based learning for the generation of transition potentials in land use change modeling / F. Sangermano in Transactions in GIS, vol 14 n° 5 (October 2010)
PermalinkUncertainty analysis for the classification of multispectral satellite images using SVMs and SOMs / F. Giacco in IEEE Transactions on geoscience and remote sensing, vol 48 n° 10 (October 2010)
PermalinkAutomatic fuzzy clustering using modified differential evolution for image classification / U. Maulik in IEEE Transactions on geoscience and remote sensing, vol 48 n° 9 (September 2010)
PermalinkBackscatter coefficient as an attribute for the classification of full-waveform airborne laser scanning data in urban areas / C. Alexander in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 5 (September - October 2010)
PermalinkElche : Une dame, des carrières et des cartes / Laurent Costa in Géomatique expert, n° 76 (01/09/2010)
PermalinkExtraction automatique des discontinuités planes à partir d'une scannérisation laser 3D en milieu rocheux / Souhail Hajri in Revue Française de Photogrammétrie et de Télédétection, n° 192 (Septembre 2010)
PermalinkLocal entropy map : a nonparametric approach to detecting spatially varying multivariate relationships / D. Guo in International journal of geographical information science IJGIS, vol 24 n° 9 (september 2010)
PermalinkUsing clustering methods in geospatial information systems / X. Wang in Geomatica, vol 64 n° 3 (September 2010)
PermalinkLes débuts de la télédétection spatiale dans la géographie française : témoignage d’un pionnier / Fernand Verger in L'information géographique, vol 74 n° 2 (août 2010)
PermalinkSemisupervised one-class support vector machine for classification of remote sensing data / Jordi Munoz-Mari in IEEE Transactions on geoscience and remote sensing, vol 48 n° 8 (August 2010)
PermalinkTerrestrial laser scanning and exploratory spatial data analysis for the mapping of weathering forms on rock art panels / B. Vogt in Geocarto international, vol 25 n° 5 (August 2010)
Permalinkvol 15 n° 4 - juillet - août 2010 - Ingénierie d'entreprise et des systèmes d'information (Bulletin de Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI) / S. Nurcan
PermalinkA semantic and language-based representation of an environmental scene / J.M. Le Yaouanc in Geoinformatica, vol 14 n° 3 (July 2010)
PermalinkA volumetric approach to change in satellite images / T. Pollard in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 7 (July 2010)
PermalinkApplication de la classification floue (fuzzy k-NN) à l'étude de l'occupation du sol d'une zone urbaine : le cas de la région de Genève / S. Rakotoniaina in Photo interprétation, European journal of applied remote sensing, vol 46 n° 2 (juin 2010)
PermalinkL'apport de l'analyse d'images à la recherche des structures socio-spatiales : application au tissu bâti beyrouthin (1956-1999) / R. Zaarour in Le monde des cartes, n° 204 (juin 2010)
PermalinkCartographier les pratiques et les usages des parisiens / J.L. Pinol in Le monde des cartes, n° 204 (juin 2010)
PermalinkEffects of topographic variability and Lidar sampling density on several DEM interpolation methods / Q. Guo in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 6 (June 2010)
PermalinkOn the integration of regional classification and delineation systems into The National Map / T. Bittner in Cartographica, vol 45 n° 2 (June 2010)
PermalinkRobust Kalman filtering with constraints: a case study for integrated navigation / Y. Yang in Journal of geodesy, vol 84 n° 6 (June 2010)
PermalinkIntegrating functional diversity into tropical forest plantation designs to study ecosystem processes / Christopher Baraloto in Annals of Forest Science, vol 67 n° 3 (2010)
PermalinkReconstruction de façades par des primitives géométriques à partir de données laser terrestres / Hakim Boulaassal in Revue Française de Photogrammétrie et de Télédétection, n° 191 (Mai 2010)
PermalinkSegmentation et interprétation de nuages de points pour la modélisation d'environnements urbains / J. Hernandez in Revue Française de Photogrammétrie et de Télédétection, n° 191 (Mai 2010)
PermalinkAlgorithms for constrained k-nearest neighbor queries over moving object trajectories / Yunjun Gao in Geoinformatica, vol 14 n° 2 (April 2010)
PermalinkAutomatic segmentation of Lidar data into coplanar point clusters using an octree-based split-and-merge algorithm / M. Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 4 (April 2010)
PermalinkDetection of roadway sign condition changes using multi-scale sign image matching (M-SIM) / Y.J. Tsai in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 4 (April 2010)
PermalinkEfficient evaluation of continuous spatio-temporal queries on moving objects whith uncertain velocity / Y. Huang in Geoinformatica, vol 14 n° 2 (April 2010)
PermalinkSome considerations on significance analysis for deformation detection via frequentist and Bayesian tests / F. Sacerdote in Journal of geodesy, vol 84 n° 4 (April 2010)
PermalinkAn improved segmentation approach for planar surfaces from undestructured 3D point clouds / T.M. Awwad in Photogrammetric record, vol 25 n° 129 (March - May 2010)
PermalinkAn interdisciplinary frame for understanding volunteered geographic information / N. Budhathoki in Geomatica, vol 64 n° 1 (March 2010)
PermalinkCommentaire de la carte des changements de l'occupation du sol dans les Rivières-du-Sud / J. Andrieu in Le monde des cartes, n° 203 (mars 2010)
PermalinkConsistency of accuracy assessment indices for soft classification: simulation analysis / J. Chen in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 2 (March - April 2010)
PermalinkExploration et représentation d'une matrice de flux / Marie Piron in Le monde des cartes, n° 203 (mars 2010)
PermalinkUn graphe génératif pour la classification semi-supervisée / P. Gaillard in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 15 n° 2 (mars - avril 2010)
PermalinkIndexation rapide de documents audio par traitement morphologique de la parole / F. Salama in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 15 n° 2 (mars - avril 2010)
PermalinkLand-cover change detection using one-class support vector machine / P. Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 3 (March 2010)
PermalinkPerceptions of virtual globes, volunteered geographical information and spatial data infrastructures / A. Cooper in Geomatica, vol 64 n° 1 (March 2010)
PermalinkSegmentation and reconstruction of polyhedral building roofs from aerial lidar points clouds / A. Sampath in IEEE Transactions on geoscience and remote sensing, vol 48 n° 3 Tome 2 (March 2010)
PermalinkTerrain modeling from Lidar range data in natural landscapes: a predictive and Bayesian framework / Frédéric Bretar in IEEE Transactions on geoscience and remote sensing, vol 48 n° 3 Tome 2 (March 2010)
PermalinkAutomatic cluster identification for environnemental applications using the self-organizing maps and a new genetic algorithm / T. Oyana in Geocarto international, vol 25 n° 1 (February 2010)
PermalinkExtending the qualitative capabilities of GIS : Computer-Aided Qualitative GIS / J. Jung in Transactions in GIS, vol 14 n° 1 (February 2010)
PermalinkFuzzy image segmentation for urban land-cover classification / I. Lizarazo in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 2 (February 2010)
PermalinkMapping an annual weed with colour-infared aerial photography and image analysis / James H. Everitt in Geocarto international, vol 25 n° 1 (February 2010)
PermalinkMultidimensional Map Algebra: design and implementation of a spatio-temporal GIS processing language / J. Mennis in Transactions in GIS, vol 14 n° 1 (February 2010)
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