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vol 57 n° 3 - December 2002 - January 2003 - Image stereoscopy and hyperspectral imaging (Bulletin de ISPRS Journal of photogrammetry and remote sensing) / A.K. Skimode
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- Radiative transfer codes applied to hyperspectral data for the retrieval of surface reflectance / K. Staenz in ISPRS Journal of photogrammetry and remote sensing, vol 57 n° 3 (December 2002 - January 2003)
- Impact of terrain slope and aspect on radargrammetric DEM accuracy / Thierry Toutin in ISPRS Journal of photogrammetry and remote sensing, vol 57 n° 3 (December 2002 - January 2003)
- Calibration and validation of SAR interferometry for DEM generation / M. Crosetto in ISPRS Journal of photogrammetry and remote sensing, vol 57 n° 3 (December 2002 - January 2003)
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Code-barres Cote Support Localisation Section Disponibilité 081-02051 SL Revue Centre de documentation Revues en salle Disponible A model-based mixture-supervised classification approach in hyperspectral data analysis / M.M. Dundar in IEEE Transactions on geoscience and remote sensing, vol 40 n° 12 (December 2002)
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Titre : A model-based mixture-supervised classification approach in hyperspectral data analysis Type de document : Article/Communication Auteurs : M.M. Dundar, Auteur ; D. Landgrebe, Auteur Année de publication : 2002 Article en page(s) : pp 2692 - 2699 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] covariance
[Termes IGN] image hyperspectraleRésumé : (Auteur) It is well known that there is a strong relation between class definition precision and classification accuracy in pattern classification applications. In hyperspectral data analysis, usually classes of interest contain one or more components and may not be well represented by a single Gaussian density function. In this paper, a model-based mixture classifier, which uses mixture models to characterize class densities, is discussed. However, a key outstanding problem of this approach is how to choose the number of components and determine their parameters for such models in practice, and to do so in the face of limited training sets where estimation error becomes a significant factor. The proposed classifier estimates the number of subclasses and class statistics simultaneously by choosing the best model. The structure of class' s covariances is also addressed through a model-based covariance estimation technique introduced in this paper. Numéro de notice : A2002-351 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2002.807010 En ligne : https://doi.org/10.1109/TGRS.2002.807010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22262
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 12 (December 2002) . - pp 2692 - 2699[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-02121 RAB Revue Centre de documentation En réserve L003 Disponible Radiative transfer codes applied to hyperspectral data for the retrieval of surface reflectance / K. Staenz in ISPRS Journal of photogrammetry and remote sensing, vol 57 n° 3 (December 2002 - January 2003)
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Titre : Radiative transfer codes applied to hyperspectral data for the retrieval of surface reflectance Type de document : Article/Communication Auteurs : K. Staenz, Auteur ; J. Secker, Auteur ; B.C. Gao, Auteur ; C. Davis, Auteur ; C. Nadeau, Auteur Année de publication : 2002 Article en page(s) : pp 194 - 203 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Airborne Visible/InfraRed Imaging Spectrometer
[Termes IGN] extraction
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] réflectance de surface
[Termes IGN] transfert radiatifRésumé : (Auteur) The present investigation evaluates surface reflectance retrieved from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Compact Airborne Spectrographic Imager (casi) data using the atmospheric radiative transfer (RT) codes: atmospheric removal program (ATREM), Canadian advanced modified 5S (CAM5S) and moderate atmospheric radiance and transmittance model (MODTRAN4). The retrieved surface reflectances were compared with groundbased reflectances acquired with a GER3700-spectroradiometer for a playa and canola target. The results showed that the best overall performance was achieved with MODTRAN4 (average relative error of 2.3%), followed by ATREM (3.6%) and CAM5S (4.2%). Major differences occur in the stronger gas absorption regions. At wavelengths unaffected by strong gaseous absorption, the performance was similar for the three RT codes even though ATREM and CAM5S make extensive use of analytical expressions and, therefore, have faster execution times. Copyright ISPRS Numéro de notice : A2002-295 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/S0924-2716(02)00121-1 En ligne : https://doi.org/10.1016/S0924-2716(02)00121-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22206
in ISPRS Journal of photogrammetry and remote sensing > vol 57 n° 3 (December 2002 - January 2003) . - pp 194 - 203[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-02051 SL Revue Centre de documentation Revues en salle Disponible Two approaches of textural classification for the location of the flows of lava on the volcanic site of the mountain Cameroon / E. Tonye in Geocarto international, vol 17 n° 4 (December 2002 - February 2003)
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Titre : Two approaches of textural classification for the location of the flows of lava on the volcanic site of the mountain Cameroon Type de document : Article/Communication Auteurs : E. Tonye, Auteur ; A. Akono, Auteur Année de publication : 2002 Article en page(s) : pp 33 - 43 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse texturale
[Termes IGN] classification dirigée
[Termes IGN] histogramme
[Termes IGN] image en couleur composée
[Termes IGN] image ERS-SAR
[Termes IGN] lave
[Termes IGN] Mont-Cameroun (volcan)
[Termes IGN] représentation cartographique
[Termes IGN] risque naturel
[Termes IGN] volcanRésumé : (Auteur) This study presents two approaches of textural classification on a synthetic aperture radar (SAR) ERS-2 image, with the aim of the location of the flows of lava and of the serviced zones around the volcanic site of the Mountain Cameroon. The first approach is a method of progressive supervised classification, where a single class is extracted at the same moment, by using 7 parameters of texture stemming from the run length method. Three classes of texture were extracted by this method and the images from the three classes were merged by the red green blue coloured composition to produce the final map. For purposes of comparison, a not supervised classification was applied to the same image. The applied not supervised classification uses parameters of texture stemming from the co-occurrence matrix method, and it lays on the detection of the peaks of a histogram. The results obtained by the two methods are coherent, and the validation of the results was made by observations during a recent mission on the site of study. Numéro de notice : A2003-049 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040208542252 En ligne : https://doi.org/10.1080/10106040208542252 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22346
in Geocarto international > vol 17 n° 4 (December 2002 - February 2003) . - pp 33 - 43[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-02041 RAB Revue Centre de documentation En réserve L003 Disponible Bayesian soft classification for sub-pixel analysis: a critical evaluation / J. Ronald Eastman in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 11 (November 2002)
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Titre : Bayesian soft classification for sub-pixel analysis: a critical evaluation Type de document : Article/Communication Auteurs : J. Ronald Eastman, Auteur ; R.M. Laney, Auteur Année de publication : 2002 Article en page(s) : pp 1149 - 1154 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] axiome de Bayes
[Termes IGN] classification
[Termes IGN] matrice de covariance
[Termes IGN] occupation du sol
[Termes IGN] pixel
[Termes IGN] probabilitésRésumé : (Auteur) Soft classifiers defer the decision about the class membership of a pixel in favor of an expression of the degree of membership it exhibits in each of the landcover classes under consideration. The reasons for using a soft classifier include the examination of classification uncertainty, but are most commonly directed to the potential of uncovering the proportional constituents of mixed pixelsa process called subpixel classification. In this study we examine the assumptions and procedures of a commonly cited Bayesian softclassification procedure for subpixel classification, and test its ability to uncover mixture proportions. The procedure involves the use of mixedcover training sites to estimate the underlying class signatures through the development of fuzzy mean reflectances and covariance matrices. These are then used to evaluate the Bayesian a posteriori probability of belonging to each landcover class. Using an artificial data set, it was found that this Bayesian softclassification procedure is unable to uncover constituent class proportions unless substantial overlap exists in the distributions of parent classes. It was found that the use of fuzzy training sites improves the accuracy of this procedure, but not because of any special insights it offers into the underlying distributions, but rather, because of its tendency to increase the degree of overlap between parent distributions. Numéro de notice : A2002-246 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans En ligne : https://www.asprs.org/wp-content/uploads/pers/2002journal/november/2002_nov_1149 [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22158
in Photogrammetric Engineering & Remote Sensing, PERS > vol 68 n° 11 (November 2002) . - pp 1149 - 1154[article] PermalinkA robust classification procedure based on mixture classifiers and nonparametric weighted feature extraction / B.C. Kuo in IEEE Transactions on geoscience and remote sensing, vol 40 n° 11 (November 2002)
PermalinkThe effect of training strategies on supervised classification at different spatial resolutions / D.M. Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 11 (November 2002)
PermalinkLandscape dynamics of the spread of sudden oak death / M. Kelly in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 10 (October 2002)
PermalinkLe procédé de navigation spatiale Transmap (R) : application à l'imagerie territoriale / Franck Perdrizet in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 168 (Octobre 2002)
PermalinkGIS and high resolution Spot imagery evaluating the impact of urbanization on agricultural lands / H. Anys in Geocarto international, vol 17 n° 3 (September - November 2002)
PermalinkImpact of contextual information integration on pixel fusion / Sophie Fabre in IEEE Transactions on geoscience and remote sensing, vol 40 n° 9 (September 2002)
PermalinkLa mouche tsé-tsé sous haute surveillance : cartographie des paysages épidémiologiques de la maladie du sommeil par télédétection et analyse spatiale / D. Laffly in XYZ, n° 92 (septembre - novembre 2002)
PermalinkA multiple-cascade-classifier system for a robust and partially unsupervised updating of land-cover maps / Lorenzo Bruzzone in IEEE Transactions on geoscience and remote sensing, vol 40 n° 9 (September 2002)
PermalinkSemi-automated extraction of rivers from digital imagery / C.R. Dillabaugh in Geoinformatica, vol 6 n° 3 (September - November 2002)
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