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Termes IGN > mathématiques > statistique mathématique
statistique mathématique
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biométrie,
échantillonnage (statistique), probabilité, statistique. >>Terme(s) spécifique(s) : analyse de régression, analyse de variance, analyse des données, analyse multivariée, analyse séquentielle, calcul d'erreur, carré latin, corrélation (statistique), efficacité asymptotique (statistique), fonction pseudo-aléatoire, loi des grands nombres, modèle linéaire (statistique), modèle non linéaire (statistique), moindre carré, physique statistique, plan d'expérience, rang et sélection (statistique), rupture (statistique), SAS (logiciel), série chronologique, statistique non paramétrique, statistique robuste, tableau de contingence, test d'hypothèses (statistique), statistique stellaire. Equiv. LCSH : Mathematical statistics. Domaine(s) : 510. |
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Experimental evaluation of positional accuracy estimates from linear network using point- and line-based testing methods / T.G. Van Niel in International journal of geographical information science IJGIS, vol 16 n° 5 (july 2002)
[article]
Titre : Experimental evaluation of positional accuracy estimates from linear network using point- and line-based testing methods Type de document : Article/Communication Auteurs : T.G. Van Niel, Auteur ; T.R. Mc Vicar, Auteur Année de publication : 2002 Article en page(s) : pp 455 - 473 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique
[Termes IGN] analyse de données
[Termes IGN] estimation de position
[Termes IGN] objet géographique linéaire
[Termes IGN] point d'appui
[Termes IGN] précision géométrique (imagerie)
[Termes IGN] primitive géométrique
[Termes IGN] propagation d'erreur
[Termes IGN] test statistiqueRésumé : (Auteur) Positional accuracy estimates of linear features based on their welldefined points can be significantly different than the accuracy estimates determined from their adjoining lines. A case study was conducted to determine both the cause of this difference as well as the relative effect of the number of points used in calculating the point-based accuracy estimate. Results showed that : (1) the difference between accuracy estimates was primarily due to dissimilar criteria for measuring closeness of primitive features ; and (2) the current US requirement of using 20 well-defined points provided a reasonable estimation of accuracy for the case study. The differences in accuracy estimates described in this study should impact both the definition of geospatial accuracy standards, and the interpretation of geographical analyses with respect to error propagation. Numéro de notice : A2002-149 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810210137022 En ligne : https://doi.org/10.1080/13658810210137022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22064
in International journal of geographical information science IJGIS > vol 16 n° 5 (july 2002) . - pp 455 - 473[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-02051 RAB Revue Centre de documentation En réserve L003 Disponible Integration of classification methods for improvement of land-cover map accuracy / XiaoHang Liu in ISPRS Journal of photogrammetry and remote sensing, vol 56 n° 4 (July - August 2002)
[article]
Titre : Integration of classification methods for improvement of land-cover map accuracy Type de document : Article/Communication Auteurs : XiaoHang Liu, Auteur ; Andrew K. Skidmore, Auteur ; H.V. Oosten, Auteur Année de publication : 2002 Article en page(s) : pp 257 - 268 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification à base de connaissances
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par réseau neuronal
[Termes IGN] occupation du solRésumé : (Auteur) Classifiers, which are used to recognize patterns in remotely sensing images, have complementary capabilities. This study tested whether integrating the results from individual classifiers improves classification accuracy. Two integrated approaches were undertaken. One approach used a consensus builder (CS13) to adjust classification output in the case of disagreement in classification between maximum likelihood classifier (MLC), expert system classifier (ESC) and neural network classifier (NNC). If the output classes for each individual pixel differed, the producer accuracies for each class were compared and the class with the highest producer accuracy was assigned to the pixel. The consensus builder approach resulted in a classification with a slightly lower accuracy (72%) when compared with the neural network classifier (74%), but it did significantly better than the maximum likelihood (62%) and expert system (59%) classifiers. The second approach integrated a rulebased expert system classifier and a neural network classifier. The output of the expert system classifier was used as one additional new input layer of the neural network classifier. A postprocessing using the producer accuracies and some additional expert rules was applied to improve the output of the integrated classifier. This is a relatively new approach in the field of image processing. This second approach produced the highest overall accuracy (80%). Thus, incorporating correct, complete and relevant expert knowledge in a neural network classifier leads to higher classification accuracy. Copyright ISPRS Numéro de notice : A2002-168 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/S0924-2716(02)00061-8 En ligne : https://doi.org/10.1016/S0924-2716(02)00061-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22083
in ISPRS Journal of photogrammetry and remote sensing > vol 56 n° 4 (July - August 2002) . - pp 257 - 268[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-02021 SL Revue Centre de documentation Revues en salle Disponible An experimental study on content-based image classication for image databases / R.D. Holowczak in IEEE Transactions on geoscience and remote sensing, vol 40 n° 6 (June 2002)
[article]
Titre : An experimental study on content-based image classication for image databases Type de document : Article/Communication Auteurs : R.D. Holowczak, Auteur ; F.J. Artigas, Auteur ; S.A. Chunfang, Auteur ; J.S. Cho, Auteur ; H.S. Stone, Auteur Année de publication : 2002 Article en page(s) : pp 1338 - 1347 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données d'images
[Termes IGN] classification dirigée
[Termes IGN] image NOAA-AVHRR
[Termes IGN] nébulosité
[Termes IGN] reconnaissance automatique
[Termes IGN] zone d'intérêtRésumé : (Auteur) Current art uses metadata associated with satellite images to facilitate their retrieval from image repositories. Typical metadata are geographic location, time, and data type. Because the metadata do not indicate which regions within an image are obscured by clouds, retrieval with such metadata may produce an image within which the region of interest (ROI) for the user is not visible. We report a system that can automatically determine whether an ROI is visible in the image, and can incorporate this into the metadata for individual images to enhance searching capability. The goal is to annotate each image with metadata regarding a number of ROIs. An experiment with the system annotated 236 advanced very high resolution radiometer (AVHRR) images of the North Atlantic from a flvemonth viewing period with descriptors that expressed the visibility of an ROI centered on Long Island, NY. For ground truth, we used the classifications of three human subjects to determine visibility of the same region of interest, and labeled the ROI with the majority decision of the three subjects. Partial cloud cover made the human determination subjective, and resulted in disagreements among the subjects. Using randomly selected training subsets of the images, we found the two images whose regions were most like those in images for which the Long Island region was visible. For training subsets, the descriptors derived from the two best images produced average recall and precision retrieval results jointly in the 75% to 80% region. Descriptors derived from those same two images for the test subsets also produced average recall and precision results that jointly fell in the 75% to 80% region. Numéro de notice : A2002-191 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2002.800751 Date de publication en ligne : 02/08/2002 En ligne : https://doi.org/10.1109/TGRS.2002.800751 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22106
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 6 (June 2002) . - pp 1338 - 1347[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-02061 RAB Revue Centre de documentation En réserve L003 Disponible 065-02062 RAB Revue Centre de documentation En réserve L003 Disponible Anomaly detection and classification for hyperspectral imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 40 n° 6 (June 2002)
[article]
Titre : Anomaly detection and classification for hyperspectral imagery Type de document : Article/Communication Auteurs : C.I. Chang, Auteur ; S.S. Chiang, Auteur Année de publication : 2002 Article en page(s) : pp 1314 - 1325 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse discriminante
[Termes IGN] capteur multibande
[Termes IGN] classification
[Termes IGN] détection d'erreur
[Termes IGN] image hyperspectrale
[Termes IGN] matrice de covarianceRésumé : (Auteur) Anomaly detection becomes increasingly important in hyperspectral image analysis, since hyperspectral imagers can now uncover many material substances which were previously unresolved by multispectral sensors. Two types of anomaly detection are of interest and considered in this paper. One was previously developed by Reed and Yu to detect targets whose signatures are distinct from their surroundings. Another was designed to detect targets with low probabilities in an unknown image scene. Interestingly, they both operate the same form as does a matched filter. Moreover, they can be implemented in realtime processing, provided that the sample covariance matrix is replaced by the sample correlation matrix. One disadvantage of an anomaly detector is the lack of ability to discriminate the detected targets from another. In order to resolve this problem, the concept of target discrimination measures is introduced to cluster different types of anomalies into separate target classes. By using these class means as target information, the detected anomalies can be further classified. With inclusion of target discrimination in anomaly detection, anomaly classification can be implemented in a threestage process, first by anomaly detection to find potential targets, followed by target discrimination to cluster the detected anomalies into separate target classes, and concluded by a classifier to achieve target classification. Experiments show that anomaly classification performs very differently from anomaly detection. Numéro de notice : A2002-189 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2002.800280 En ligne : https://doi.org/10.1109/TGRS.2002.800280 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22104
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 6 (June 2002) . - pp 1314 - 1325[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-02061 RAB Revue Centre de documentation En réserve L003 Disponible 065-02062 RAB Revue Centre de documentation En réserve L003 Disponible Cognitive geometry for cartography / J. Comenetz in Cartographic journal (the), vol 39 n° 1 (June 2002)
[article]
Titre : Cognitive geometry for cartography Type de document : Article/Communication Auteurs : J. Comenetz, Auteur Année de publication : 2002 Article en page(s) : pp 65 - 75 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie numérique
[Termes IGN] classification dirigée
[Termes IGN] géométrie
[Termes IGN] système d'information géographique
[Termes IGN] visualisation cartographiqueRésumé : (Auteur) The standard model of the geometry of cartographic visualization in geographic information systems (GISs) is based on the classification of cartographic objects into points, lines, and polygons, represented with zero, one, and two dimensional symbols. This is restrictive because an object or symbol may actually span more than one of these dimensional categories or may occupy an intermediate position between categories. A more complete, 'cognitive' model of the geometry of visualization is proposed here. The new model is more flexible because it permits a symbol or object to be positioned anywhere within several continua between the standard dimensional categories. Numéro de notice : A2002-174 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1179/caj.2002.39.1.65 En ligne : https://www.tandfonline.com/doi/abs/10.1179/caj.2002.39.1.65 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22089
in Cartographic journal (the) > vol 39 n° 1 (June 2002) . - pp 65 - 75[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 030-02011 RAB Revue Centre de documentation En réserve L003 Disponible Comparative evaluation of Indian remote sensing multi-spectral sensors data for crop classification / R.P. Singh in Geocarto international, vol 17 n° 2 (June - August 2002)PermalinkÉtude par télédétection aéroportée d’un environnement lagunaire en zone tropicale : cas de la lagune Ébrié en Côte d’Ivoire / Éric Valère Djagoua in Télédétection : revue de recherche et d'application en télédétection, vol 2 n° 4 ([01/06/2002])PermalinkFusion radar and optical data for land cover mapping / Nathaniel D. Herold in Geocarto international, vol 17 n° 2 (June - August 2002)PermalinkIdentifier les zones noires d'un réseau routier par l'autocorrélation spatiale locale : analyses de sensibilité et aspects opérationnels / Benoit Flahaut in Revue internationale de géomatique, vol 12 n° 2 (juin - août 2002)PermalinkLarge-area land-cover mapping through scene-based classification compositing / B. Guindon in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 6 (June 2002)PermalinkLa naissance d’un service public : l’Inventaire forestier national (1960-1963) / Roger Balleydier in Revue forestière française, vol 54 n° 3 (Juin 2002)PermalinkPrincipal component analysis for hyperspectral image classification / C. Rodarmel in Surveying and land information systems, vol 62 n° 2 (01/06/2002)PermalinkTextural and contextual land-cover classification using single and multiple classifier systems / O. Debeir in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 6 (June 2002)PermalinkThe constrained signal detector / S. Johnson in IEEE Transactions on geoscience and remote sensing, vol 40 n° 6 (June 2002)PermalinkThe role of remote sensing and GIS in enforcement of areas of permanent preservation in the Brazilian Amazon / L.A. Firestone in Geocarto international, vol 17 n° 2 (June - August 2002)Permalink