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Land covers update by supervised classification of segmented ASTER images / A.R.S. Marcal in International Journal of Remote Sensing IJRS, vol 26 n° 7 (April 2005)
[article]
Titre : Land covers update by supervised classification of segmented ASTER images Type de document : Article/Communication Auteurs : A.R.S. Marcal, Auteur ; J.S. Borges, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 1347 - 1362 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse discriminante
[Termes IGN] carte d'occupation du sol
[Termes IGN] classificateur paramétrique
[Termes IGN] classification barycentrique
[Termes IGN] classification dirigée
[Termes IGN] classification floue
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image multibande
[Termes IGN] image Terra-ASTER
[Termes IGN] mise à jour cartographique
[Termes IGN] Portugal
[Termes IGN] segmentation d'imageRésumé : (Auteur) The revision of the 1995 land cover dataset for the Vale do Sousa region, in the northwest of Portugal, was carried out by supervised classification of a multispectral image from the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) sensor. The nine reflective bands of ASTER were used, covering the spectral range from 0.52-2.43 um. The image was initially ortho-rectified and segmented into 51 186 objects, with an average object size of 135 pixels (about 3 ha). A total of 582 of these objects were identified for training nine land cover classes. The image was classified using an algorithm based on a fuzzy classifier, Support Vector Machines (SVM), K Nearest Neighbours (K-NN) and a Logistic Discrimination (LD) classifier. The results from the classification were evaluated using a set of 277 validation sites, independently gathered. The overall accuracy was 44.6%, for the fuzzy classifier. 70.5%, for the SVM, 60.9% for the K-NN and 72.2% for the LD classifier. The difficulty in discriminating between some of the forest land cover classes was examined by separability analysis and unsupervised classification with hierarchical clustering. The forest classes were found to overlap in the multi-spectral space defined by the nine ASTER bands used. Numéro de notice : A2005-179 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160412331291233 En ligne : https://doi.org/10.1080/01431160412331291233 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27316
in International Journal of Remote Sensing IJRS > vol 26 n° 7 (April 2005) . - pp 1347 - 1362[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05071 RAB Revue Centre de documentation En réserve L003 Exclu du prêt SPOT-4 Vegetation multi-temporal compositing for land cover change studies over tropical regions / João M.B. Carreiras in International Journal of Remote Sensing IJRS, vol 26 n° 7 (April 2005)
[article]
Titre : SPOT-4 Vegetation multi-temporal compositing for land cover change studies over tropical regions Type de document : Article/Communication Auteurs : João M.B. Carreiras, Auteur ; J.M.C. Pereira, Auteur Année de publication : 2005 Article en page(s) : pp 1323 - 1346 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes principales
[Termes IGN] autocorrélation spatiale
[Termes IGN] cohérence des données
[Termes IGN] détection de changement
[Termes IGN] filtrage du bruit
[Termes IGN] forêt tropicale
[Termes IGN] image multitemporelle
[Termes IGN] image optique
[Termes IGN] image SPOT-Végétation
[Termes IGN] Mato Grosso
[Termes IGN] nébulosité
[Termes IGN] rapport signal sur bruit
[Termes IGN] Soil Adjusted Vegetation Index
[Termes IGN] surveillance agricole
[Termes IGN] utilisation du sol
[Termes IGN] zone intertropicaleRésumé : (Auteur) Multi-temporal compositing of SPOT-4 VEGETATION imagery over tropical regions was tested to produce spatially coherent monthly composite images with reduced cloud contamination, for the year 2000. Monthly composite images generated from daily images (S1 product, 1-km) encompassing different land cover. types of the state of Mato Grosso, Brazil, were evaluated in terms of cloud contamination and spatial consistency. A new multi-temporal compositing algorithm was tested which uses different criteria for vegetated and non-vegetated or sparsely vegetated land cover types. Furthermore, a principal components transformation that rescales the noise in the image-Maximum Noise Fraction (MNF)- was applied to a multi-temporal dataset of monthly composite images and tested as a method of additional signal-to-noise ratio improvement. The back-transformed dataset using the first 12 MNF eigenimages yielded an accurate reconstruction of monthly composite images from the dry season (May to September) and enhanced spatial coherence from wet season images (October to April), as evaluated by the Moran's 1 index of spatial autocorrelation. This approach is useful for land cover- change studies in the tropics, where it is difficult to obtain cloud-free optical remote sensing imagery. In Mato Grosso, wet season composite images are important for monitoring agricultural crop cycles. Numéro de notice : A2005-178 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331338005 En ligne : https://doi.org/10.1080/01431160512331338005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27315
in International Journal of Remote Sensing IJRS > vol 26 n° 7 (April 2005) . - pp 1323 - 1346[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05071 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Integration of spatial and spectral information by means of unsupervised extraction and classification for homogenous objects applied to multispectral and hyperspectral data / L.O. Jimenez in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)
[article]
Titre : Integration of spatial and spectral information by means of unsupervised extraction and classification for homogenous objects applied to multispectral and hyperspectral data Type de document : Article/Communication Auteurs : L.O. Jimenez, Auteur ; J.L. Rivera-Medina, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 844 - 851 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse multivariée
[Termes IGN] classification contextuelle
[Termes IGN] classification non dirigée
[Termes IGN] classification orientée objet
[Termes IGN] extraction automatique
[Termes IGN] image à haute résolution
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] intégration de données
[Termes IGN] objet homogèneRésumé : (Auteur) This paper presents a method of unsupervised enhancement of pixels homogeneity in a local neighborhood. This mechanism will enable an unsupervised contextual classification of multispectral data that integrates the spectral and spatial information producing results that are more meaningful to the human analyst. This unsupervised classifier is an unsupervised development of the well-known supervised extraction and classification for homogenous objects (ECHO) classifier. One of its main characteristics is that it simplifies the retrieval process of spatial structures. This development is specially relevant for the new generation of airborne and spaceborne sensors with high spatial resolution. Numéro de notice : A2005-192 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2004.843193 En ligne : https://doi.org/10.1109/TGRS.2004.843193 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27329
in IEEE Transactions on geoscience and remote sensing > vol 43 n° 4 (April 2005) . - pp 844 - 851[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-05042 RAB Revue Centre de documentation En réserve L003 Disponible Multivariate analysis and geovisualization with an integrated geographic knowledge discovery approach / D. Guo in Cartography and Geographic Information Science, vol 32 n° 2 (April 2005)
[article]
Titre : Multivariate analysis and geovisualization with an integrated geographic knowledge discovery approach Type de document : Article/Communication Auteurs : D. Guo, Auteur ; M. Gahegan, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 113 - 132 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique
[Termes IGN] analyse multivariée
[Termes IGN] carte de Kohonen
[Termes IGN] découverte de connaissances
[Termes IGN] données cartographiques
[Termes IGN] échantillon
[Termes IGN] interactivité
[Termes IGN] visualisation de donnéesRésumé : (Auteur) The discovery, interpretation, and presentation of multivariate spatial patterns are important for scientific understanding of complex geographic problems. This research integrates computational, visual, and cartographic methods together to detect and visualize multivariate spatial patterns. The integrated approach is able to: (1) perform multivariate analysis, dimensional reduction, and data reduction (summarizing a large number of input data items in a moderate number of clusters) with the Self-Organizing Map (SOM); (2) encode the SOM result with a systematically designed color scheme; (3) visualize the multivariate patterns with a modified Parallel Coordinate Plot (PCP) display and a geographic map (GeoMap); and (4) support human interactions to explore and examine patterns. The research shows that such "mixed initiative" methods (computational and visual) can mitigate each other's weakness and collaboratively discover complex patterns in large geographic datasets, in an effective and efficient way. Numéro de notice : A2005-191 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1559/1523040053722150 En ligne : https://doi.org/10.1559/1523040053722150 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27328
in Cartography and Geographic Information Science > vol 32 n° 2 (April 2005) . - pp 113 - 132[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-05021 RAB Revue Centre de documentation En réserve L003 Disponible Remote sensing image thresholding methods for determining landslide activity / P.L. Rosin in International Journal of Remote Sensing IJRS, vol 26 n° 6 (March 2005)
[article]
Titre : Remote sensing image thresholding methods for determining landslide activity Type de document : Article/Communication Auteurs : P.L. Rosin, Auteur ; J. Hervas, Auteur Année de publication : 2005 Article en page(s) : pp 1075 - 1092 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] analyse de groupement
[Termes IGN] effondrement de terrain
[Termes IGN] filtrage numérique d'image
[Termes IGN] image satellite
[Termes IGN] Italie
[Termes IGN] orthorectification
[Termes IGN] seuillage d'imageRésumé : (Auteur) Detecting landslides and monitoring their activity is of great relevance for disastrer prevention, preparedness and mitigation in hilly areas. To this end, change detection techniques were developed and applied to multi-temporal digital aerial photographs, simulating the very high spatial resolution of new satellite sensor optical imagery, over the Tessina complex landslide in north-eastern Italy. Several automatic thresholding algorithms are compared on the difference orthorectified and radiometrically normalized images, including some standard methods based on clustering, statistics, moment and entropy, as well as some more novel techniques previously developed by the authors. In addition, a variety of filters were employed to eliminate much of the underisable residual clutter in the thresholded difference image, mainly as a result of natural vegetation and man-land cover changes. These filters are based on shape and size properties of the connected sets of pixels in the threshold maps. This has enabled us discriminate most ground surface changes related to the movement of a pre-existing landslide. Numéro de notice : A2005-144 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331330481 En ligne : https://doi.org/10.1080/01431160512331330481 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27282
in International Journal of Remote Sensing IJRS > vol 26 n° 6 (March 2005) . - pp 1075 - 1092[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05061 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Mapping tropical forest structure in south-eastern Madagascar using remote sensing and artificial neural networks / J.C. Ingram in Remote sensing of environment, vol 94 n° 4 (28/02/2005)PermalinkSatellite image classification using genetically guided fuzzy clustering with spatial information / S. Bandyopadhyay in International Journal of Remote Sensing IJRS, vol 26 n° 3 (February 2005)PermalinkAgriculture classification using PolSAR data / H. Skriver (2005)PermalinkNon rigid registration of shapes via diffeomorphic point matching and clustering / Laurent Garcin (2005)PermalinkTélédétection et paludisme urbain / Laurence Jolivet (2005)PermalinkA texture orientation estimator for discriminating between forests, orchards, vineyards, and tilled fields / Roger Trias-Sanz (2005)PermalinkDiscrimination potential of X-band polarimetric SAR data / Nicolas Baghdadi in International Journal of Remote Sensing IJRS, vol 25 n° 22 (November 2004)PermalinkFiltering airborne Laser scanner data: a wavelet-based clustering method / T. Thuy in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 11 (November 2004)PermalinkSpectral mixture analysis of the urban landscape in Indianapolis with Landsat ETM+ imagery / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 9 (September 2004)PermalinkDerivation of a threshold function for the advanced very high resolution radiometer 3, 75um channel and its application in automatic cloud discrimination over snow/ice surfaces / X. Xiong in International Journal of Remote Sensing IJRS, vol 25 n° 15 (August 2004)Permalink