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Segmentation hyperspectrale de forêts tropicales par arbres de partition binaires / Guillaume Tochon in Revue Française de Photogrammétrie et de Télédétection, n° 202 (Avril 2013)
[article]
Titre : Segmentation hyperspectrale de forêts tropicales par arbres de partition binaires Type de document : Article/Communication Auteurs : Guillaume Tochon, Auteur ; Jean-Baptiste Féret, Auteur ; Silvia Valero, Auteur ; Philippe Salembier, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 55 - 65 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] arbre BSP
[Termes IGN] arbre-B
[Termes IGN] forêt tropicale
[Termes IGN] Hawaii (Etats-Unis)
[Termes IGN] image hyperspectrale
[Termes IGN] Panama
[Termes IGN] segmentation d'imageRésumé : (Auteur) La segmentation d'images de forêts tropicales est un outil important pour faciliter le travail des écologues. Dans ce papier, nous proposons une nouvelle méthode de segmentation pour les images hyperspectrales, basée sur la construction d'un arbre de partition binaire (APB). Nous introduisons tout d'abord une étape de prétraitement combinant une analyse en composantes principales et la définition de cartes de pré-segmentation, afin de réduire spatialement et spectralement le volume de données à traiter. La construction de l'APB nécessite la définition d'un modèle de région statistique non-paramétrique s'appuyant sur des histogrammes, ainsi qu'un critère de fusion fondé sur la distance de diffusion. Nous introduisons également une stratégie d'élagage de l'APB, adaptée spécifiquement à la segmentation de couronnes d'arbres en forêts tropicales. Pour finir, nous présentons certains critères permettant d'évaluer la qualité de la segmentation finale, basés sur le décompte du nombre de couronnes de référence correctement segmentées. La méthode proposée est validée sur deux jeux de données issues de campagnes aéroportées à Hawaii et Panama, respectivement, avec des résolutions spectrales et spatiales différentes. Numéro de notice : A2013-316 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.52638/rfpt.2013.51 En ligne : https://doi.org/10.52638/rfpt.2013.51 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32454
in Revue Française de Photogrammétrie et de Télédétection > n° 202 (Avril 2013) . - pp 55 - 65[article]STARS : 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)
[article]
Titre : STARS : A new method for multitemporal remote sensing Type de document : Article/Communication Auteurs : Marcio Pupin Mello, Auteur ; CARLOS A.O. Vieira, Auteur Année de publication : 2013 Article en page(s) : pp 1897 - 1913 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] Brésil
[Termes IGN] collocation
[Termes IGN] données multitemporelles
[Termes IGN] image multibande
[Termes IGN] procédure opérationnelle
[Termes IGN] réflectance de surface
[Termes IGN] Saccharum officinarumRésumé : (Auteur) There is great potential for the development of remote sensing methods that integrate and exploit both multispectral and multitemporal information. This paper presents a new image processing method: Spectral–Temporal Analysis by Response Surface (STARS), which synthesizes the full information content of a multitemporal–multispectral remote sensing image data set to represent the spectral variation over time of features on the Earth's surface. Depending on the application, STARS can be effectively implemented using a range of different models [e.g., polynomial trend surface (PTS) and collocation surface (CS)], exploiting data from different sensors, with varying spectral wavebands and acquiring data at irregular time intervals. A case study was used to test STARS, evaluating its potential to characterize sugarcane harvest practices in Brazil, specifically with and without preharvest straw burning. Although the CS model presented sharper and more defined spectral–temporal surfaces, abrupt changes related to the sugarcane harvest event were also well characterized with the PTS model when a suitable degree was set. Orthonormal coefficients were tested for both the PTS and CS models and performed more accurately than regular coefficients when used as input for three evaluated classifiers: instance based, decision tree, and neural network. Results show that STARS holds considerable potential for representing the spectral changes over time of features on the Earth's surface, thus becoming an effective image processing method, which is useful not only for classification purposes but also for other applications such as understanding land-cover change. The STARS algorithm can be found at www.dsr.inpe.br/~mello. Numéro de notice : A2013-211 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2215332 En ligne : https://doi.org/ 10.1109/TGRS.2012.2215332 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32349
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 4 Tome 1 (April 2013) . - pp 1897 - 1913[article]Assessment 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)
[article]
Titre : Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study Type de document : Article/Communication Auteurs : Gyanesh Chander, Auteur ; Dennis L. Helder, Auteur ; David Aaron, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 1282 - 1296 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] bande spectrale
[Termes IGN] étalonnage relatif
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectrale
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] image Terra-MODIS
[Termes IGN] incertitude de mesurage
[Termes IGN] incertitude géométrique
[Termes IGN] incertitude spectrale
[Termes IGN] Libye
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] réponse spectraleRésumé : (Auteur) Cross-calibration of satellite sensors permits the quantitative comparison of measurements obtained from different Earth Observing (EO) systems. Cross-calibration studies usually use simultaneous or near-simultaneous observations from several spaceborne sensors to develop band-by-band relationships through regression analysis. The investigation described in this paper focuses on evaluation of the uncertainties inherent in the cross-calibration process, including contributions due to different spectral responses, spectral resolution, spectral filter shift, geometric misregistrations, and spatial resolutions. The hyperspectral data from the Environmental Satellite SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY and the EO-1 Hyperion, along with the relative spectral responses (RSRs) from the Landsat 7 Enhanced Thematic Mapper (TM) Plus and the Terra Moderate Resolution Imaging Spectroradiometer sensors, were used for the spectral uncertainty study. The data from Landsat 5 TM over five representative land cover types (desert, rangeland, grassland, deciduous forest, and coniferous forest) were used for the geometric misregistrations and spatial-resolution study. The spectral resolution uncertainty was found to be within 0.25%, spectral filter shift within 2.5%, geometric misregistrations within 0.35%, and spatial-resolution effects within 0.1% for the Libya 4 site. The one-sigma uncertainties presented in this paper are uncorrelated, and therefore, the uncertainties can be summed orthogonally. Furthermore, an overall total uncertainty was developed. In general, the results suggested that the spectral uncertainty is more dominant compared to other uncertainties presented in this paper. Therefore, the effect of the sensor RSR differences needs to be quantified and compensated to avoid large uncertainties in cross-calibration results. Numéro de notice : A2013-124 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2228008 En ligne : https://doi.org/10.1109/TGRS.2012.2228008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32262
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 3 Tome 1 (March 2013) . - pp 1282 - 1296[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013031A RAB Revue Centre de documentation En réserve L003 Disponible GSICS 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)
[article]
Titre : GSICS inter-calibration of infrared channels of geostationary imagers using Metop-IASI Type de document : Article/Communication Auteurs : Tim J. Hewison, Auteur ; Xiangqian Wu, Auteur ; Fangfang Yu, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 1160 - 1170 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] erreur systématique
[Termes IGN] étalonnage relatif
[Termes IGN] image Feng-Yun
[Termes IGN] image GOES
[Termes IGN] image hyperspectrale
[Termes IGN] image Météosat
[Termes IGN] image MetOp-IASI
[Termes IGN] image thermique
[Termes IGN] rayonnement infrarouge thermique
[Termes IGN] régression linéaireRésumé : (Auteur) The first products of the Global Space-based Inter-Calibration System (GSICS) include bias monitoring and calibration corrections for the thermal infrared (IR) channels of current meteorological sensors on geostationary satellites. These use the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) on the low Earth orbit (LEO) Metop satellite as a common cross-calibration reference. This paper describes the algorithm, which uses a weighted linear regression, to compare collocated radiances observed from each pair of geostationary-LEO instruments. The regression coefficients define the GSICS Correction, and their uncertainties provide quality indicators, ensuring traceability to the selected community reference, IASI. Examples are given for the Meteosat, GOES, MTSAT, Fengyun-2, and COMS imagers. Some channels of these instruments show biases that vary with time due to variations in the thermal environment, stray light, and optical contamination. These results demonstrate how inter-calibration can be a powerful tool to monitor and correct biases, and help diagnose their root causes. Numéro de notice : A2013-123 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2238544 En ligne : https://doi.org/10.1109/TGRS.2013.2238544 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32261
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 3 Tome 1 (March 2013) . - pp 1160 - 1170[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013031A RAB Revue Centre de documentation En réserve L003 Disponible Learning 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)
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Titre : Learning with transductive SVM for semisupervised pixel classification of remote sensing imagery Type de document : Article/Communication Auteurs : Ujjwal Maulik, Auteur ; Debasis Chakraborty, Auteur Année de publication : 2013 Article en page(s) : pp 66 - 78 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Bombay
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] classification pixellaire
[Termes IGN] classification semi-dirigée
[Termes IGN] image infrarouge couleur
[Termes IGN] image SPOT
[Termes IGN] Inde
[Termes IGN] villeRésumé : (Auteur) Land cover classification using remotely sensed data requires robust classification methods for the accurate mapping of complex land cover area of different categories. In this regard, support vector machines (SVMs) have recently received increasing attention. However, small number of training samples remains a bottleneck to design suitable supervised classifiers. On the other hand, adequate number of unlabeled data is available in remote sensing images which can be employed as additional source of information about margins. To fully leverage all of the precious unlabeled data, integration of filtering in a transductive SVM is proposed. Using two labeled image datasets of small size and two large unlabeled image datasets, the effectiveness of the proposed method is explored. Experimental results show that the proposed technique achieves average overall accuracies of around 4.5–7.8%, 0.8–2.6% and 0.9–2.2% more than the standard inductive SVM (ISVM), progressive transductive SVM (PTSVM) and low density separation (LDS) classifiers, respectively on larger domains in case of labeled datasets. Using image datasets, visual interpretation from the classified images as well as the segmentation quality reveal that the proposed method can efficiently filter informative data from the unlabeled samples. Numéro de notice : A2013-116 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.12.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.12.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32254
in ISPRS Journal of photogrammetry and remote sensing > vol 77 (March 2013) . - pp 66 - 78[article]Réservation
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Farzam in IEEE Transactions on geoscience and remote sensing, vol 49 n° 9 (September 2011)PermalinkLa carte forestière version 2 à l'IFN : de la réalisation à la diffusion / Thierry Touzet in Rendez-vous techniques, n° 32 (printemps 2011)PermalinkIn situ estimation of water quality parameters in freshwater aquaculture ponds using hyperspectral imaging system / Amr Abd-Elrahman in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 4 (July - August 2011)PermalinkA multispectral and multiscale morphological index for automatic building extraction from multispectral GeoEye-1 imagery / X. Huang in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 7 (July 2011)PermalinkIntegration of panoramic hyperspectral imaging with terrestrial lidar data / T. Kurz in Photogrammetric record, vol 26 n° 134 (June - August 2011)PermalinkThe application of ASTER imageries and mathematical evaluation method in detecting cyanobacteria in biological soil crust, Chadormalu area, Central Iran / A. Moghtaderi in Photo interprétation, European journal of applied remote sensing, vol 47 n° 2 - 3 (juin 2011)PermalinkDétection de bateaux dans les images satellitaires optiques panchromatiques / N. Proia in Revue Française de Photogrammétrie et de Télédétection, n° 194 (Mai 2011)PermalinkA new pan-sharpening method using multiobjective particle swarm optimization and the shiftable contourlet transform / J. Saeedi in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 3 (May - June 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)PermalinkLimitless potential of geospatial imagery / P. Mcintosh in Geoinformatics, vol 14 n° 2 (01/03/2011)PermalinkImpervious surface area extraction from IKONOS imagery using an object-based fuzzy method / Xuefei Hu in Geocarto international, vol 26 n° 1 (February 2011)PermalinkDelineation of impervious surface from multispectral imagery and lidar incorporating knowledge based expert system rules / K. Germaine in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 1 (January 2011)PermalinkA hybrid classification scheme for mining multisource geospatial data / R. Vatsavai in Geoinformatica, vol 15 n° 1 (January 2011)PermalinkIntégration de la géophysique et de la télédétection pour la cartographie des sols à haute résolution spatiale : exemple de la reconnaissance de paléochenaux historiques dans les marais charentais / A. Camus in Revue Française de Photogrammétrie et de Télédétection, n° 193 (Janvier 2011)PermalinkLand cover classification of cloud-contaminated multitemporal high-resolution images / A. Salberg in IEEE Transactions on geoscience and remote sensing, vol 49 n° 1 Tome 2 (January 2011)PermalinkOn the capability of very high resolution satellite and ground probing radar techniques for detecting buried archaeological adobe structures / Rosa Lasaponara in Revue Française de Photogrammétrie et de Télédétection, n° 193 (Janvier 2011)PermalinkOrthorectification of VHR optical satellite data exploiting the geometric accuracy of TerraSAR-X data / Peter Reinartz in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 1 (January - February 2011)PermalinkRelevance of airborne lidar and multispectral image data for urban scene classification using random forests / Li Guo in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 1 (January - February 2011)PermalinkLa carte forestière sans papier / Thierry Touzet in Le monde des cartes, n° 206 (décembre 2010)Permalink