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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)
[article]
Titre : Comparative evaluation of Indian remote sensing multi-spectral sensors data for crop classification Type de document : Article/Communication Auteurs : R.P. Singh, Auteur ; V.N. Sridhar, Auteur ; V.K. Dadhwal, Auteur ; R.P. Navalgund, Auteur ; K.P. Singh, Auteur Année de publication : 2002 Article en page(s) : pp 5 - 9 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] bande rouge
[Termes IGN] bande spectrale
[Termes IGN] blé (céréale)
[Termes IGN] capteur multibande
[Termes IGN] classification automatique
[Termes IGN] cultures
[Termes IGN] données localisées numériques
[Termes IGN] image IRS-LISS
[Termes IGN] limite de résolution géométrique
[Termes IGN] production agricole
[Termes IGN] rayonnement proche infrarougeRésumé : (Auteur) Digital data from four multi spectral sensors having different spatial resolution and spectral channel, LISS-III, LISS-II, LISS-I and WiFS acquired from two Indian Remote Sensing satellite platform ( IRS 1B, IRS IC) were evaluated for wheat crop classification accuracy over central India. Classification accuracy was assessed at different spatial resolutions using common red and near infrared (nir) bands in the above four sensors data as well as simulated intermediate resolution data. It was observed that accuracy improved with better spatial resolution and there was a considerable increases in accuracy from 188 to 144 in resolution and from 72 in up to 23 m resolution with the modest increase in the intermediate range. Inclusion of the MIR band, and choice of proper acquisition date resulted in significantly higher crop classification accuracies. The results have been evaluated against the future sensor planned on IRS Platform. Numéro de notice : A2002-224 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040208542230 En ligne : https://doi.org/10.1080/10106040208542230 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22138
in Geocarto international > vol 17 n° 2 (June - August 2002) . - pp 5 - 9[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-02021 RAB Revue Centre de documentation En réserve L003 Disponible Fusion radar and optical data for land cover mapping / Nathaniel D. Herold in Geocarto international, vol 17 n° 2 (June - August 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)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 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)PermalinkThe UK land cover map 2000: construction of a parcel-based vector map from satellite images / R.M. Fuller in Cartographic journal (the), vol 39 n° 1 (June 2002)PermalinkEstimation interactive de l'indice foliaire à l'échelle régionale par décomposition "sub-pixelaire" du signal Spot4-Végétation / Fabrice Cipriani in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 167 (Avril 2002)PermalinkImagerie spatiale et aménagements forestiers au Gabon / Marcellin Nziengui in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 167 (Avril 2002)PermalinkMultiple classifier systems for supervised remote sensing image classification based on dynamic classifier selection / P.C. Smits in IEEE Transactions on geoscience and remote sensing, vol 40 n° 4 (April 2002)PermalinkAssessing effects of input uncertainty in structural landscape classification / Frank Canters in International journal of geographical information science IJGIS, vol 16 n° 2 (march 2002)PermalinkContrôle de qualité des modèles numériques des bases de données géographiques / J.F. Zelasco in XYZ, n° 90 (mars - mai 2002)PermalinkThe utility of very high spatial resolution images to identify urban objects / Anne Puissant in Geocarto international, vol 17 n° 1 (March - May 2002)PermalinkApplication of remote sensing to enhance the control of wildlife associated mycobacterium bovis infection / J.S. Mckenzie in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 2 (February 2002)PermalinkCloud tracking by scale space classification / D.P. Mukherjee in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)PermalinkComparison of GENIE and conventional supervised classifiers for multispectral image feature extraction / N.R. Harvey in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)PermalinkA derivative-aided hyperspectral image analysis system for land-cover classification / F. Tsai in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)PermalinkFuzzy rule-based classification of remotely sensed imagery / A. Bardossy in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)PermalinkLinear spectral random mixture analysis for hyperspectral imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 40 n° 2 (February 2002)PermalinkL'analyse des données / J.M. Bouroche (2002)PermalinkAnalyse d'images aériennes haute résolution pour la reconstruction de scènes urbaines / Matthieu Cord in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 166 (Janvier 2002)Permalink