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Apport de la classification combinée supervisée et non supervisée d'une image Landsat ETM+ à la cartographie géologique de la boutonnière de Kerdous, anti-atlas, Maroc / M. Hakdaoui in Photo interprétation, vol 42 n° 2 (Juin 2006)
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Titre : Apport de la classification combinée supervisée et non supervisée d'une image Landsat ETM+ à la cartographie géologique de la boutonnière de Kerdous, anti-atlas, Maroc Type de document : Article/Communication Auteurs : M. Hakdaoui, Auteur ; A. Rahimi, Auteur Année de publication : 2006 Article en page(s) : pp 46 - 51 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Atlas marocain
[Termes IGN] carte géologique
[Termes IGN] classification dirigée
[Termes IGN] classification hybride
[Termes IGN] classification ISODATA
[Termes IGN] classification non dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] image Landsat-ETM+
[Termes IGN] Maroc
[Termes IGN] modèle numérique de terrainRésumé : (Auteur) Cette étude vise à développer un algorithme de classification hybride en combinant deux approches : supervisée en utilisant la règle de maximum de vraisemblance et non supervisée en utilisant la technique ISODATA. Nous avons testé cette méthodologie sur la boutonnière de Kerdous en utilisant les données du capteur Landsat ETM+. La classification est en accord avec la carte réalisée par photo-interprétation. Cependant, des anomalies d'affectation persistent et qui nécessitent une vérification sur le terrain. Notre technique combinée permet d'améliorer la discrimination de nouveaux faciès géologiques avec des surfaces plus homogènes et moins bruitées. Elle contribue à la réorientation des travaux de cartographie et à la révision des idées sur l'évolution méga-structurale de cette région. Copyright Editions Eska Numéro de notice : A2006-526 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28249
in Photo interprétation > vol 42 n° 2 (Juin 2006) . - pp 46 - 51[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 104-06021 RAB Revue Centre de documentation En réserve L003 Disponible Artificial neural networks for mapping regional-scale upland vegetation from high spatial resolution imagery / H. Mills in International Journal of Remote Sensing IJRS, vol 27 n° 11 (June 2006)
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Titre : Artificial neural networks for mapping regional-scale upland vegetation from high spatial resolution imagery Type de document : Article/Communication Auteurs : H. Mills, Auteur ; M.E. Cutler, Auteur ; David Fairbairn, Auteur Année de publication : 2006 Article en page(s) : pp 2177 - 2195 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte de la végétation
[Termes IGN] classification par réseau neuronal
[Termes IGN] données de terrain
[Termes IGN] image à résolution métrique
[Termes IGN] image Ikonos
[Termes IGN] montagne
[Termes IGN] Perceptron multicouche
[Termes IGN] Royaume-UniRésumé : (Auteur) Upland vegetation represents an important resource that requires frequent monitoring. However, the heterogeneous nature of upland vegetation and lack of ground data require classification techniques that have a high degree of generalization ability. This study investigates the use of artificial neural networks as a means of mapping upland vegetation from remotely sensed data. First, the optimum size of support to map upland vegetation was estimated as being less than 4 m, which suggested that soft classification techniques and high spatial resolution IKONOS imagery were required. The use of high spatial resolution imagery for regional-scale areas has introduced new challenges to the remote sensing community, such as using limited ground data and mapping land-cover dynamics and variation over large areas. This work then investigated the utility of artificial neural networks (ANN) for regional-scale upland vegetation from IKONOS imagery using limited ground data and to map unseen data from remote geographical locations. A Multiple Layer Perceptron was trained with pixels from an IKONOS image using early stopping; however, despite high classification accuracies when calculated for pixels from an area where training pixels were extracted, the networks did not produce high accuracies when applied to unseen data from a remote area. Copyright Taylor & Francis. Numéro de notice : A2006-299 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500396501 En ligne : https://doi.org/10.1080/01431160500396501 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28026
in International Journal of Remote Sensing IJRS > vol 27 n° 11 (June 2006) . - pp 2177 - 2195[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-06061 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Classification of fully polarimetric SAR data for land use cartography / Cédric Lardeux in Revue Française de Photogrammétrie et de Télédétection, n° 182 (Juin 2006)
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contenu dans ISPRS Commission 1 Symposium 2006, Paris, Marne-la-Vallée, 3-6 Juillet 2006: Des capteurs à l'imagerie, vol 1. Proceedings / Alain Baudoin (2006)
Titre : Classification of fully polarimetric SAR data for land use cartography Type de document : Article/Communication Auteurs : Cédric Lardeux, Auteur ; Pierre-Louis Frison , Auteur ; Jean-Paul Rudant
, Auteur ; et al., Auteur
Année de publication : 2006 Conférence : ISPRS 2006, Commission 1 Symposium, From sensors to imagery 03/07/2006 06/07/2006 Champs-sur-Marne [Paris Marne-la-Vallée] France OA ISPRS Archives Article en page(s) : pp 23 - 27 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] bande P
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données polarimétriques
[Termes IGN] image AIRSAR
[Termes IGN] polarimétrie radar
[Termes IGN] Polynésie françaiseRésumé : (Auteur) French Polynesia islands are located at the middle of the South Pacific Ocean. They are thus subject to a strong environmental planning leading to landscape changes as well as to the introduction of invasive species. This study comes within the framework of the global cartography and inventory of the Polynesian landscape. An AIRSAR airborne mission took place in August 2000 over the main Polynesian islands. Polarimetric SAR data are particularly adapted to the cloudy conditions generally encountered over the South Pacific Islands. Fully polarimetric data allows the analysis of a geometrical and physical point of view. Different decompositions, such as H/A/a or based on the Pauli formalism have shown their potential for such applications. In order to apply these indicators and to produce a semi-automatic cartography of the Tubuai Island, we choose to use the SVM (Support Vector Machine) as supervised classifier. These results are also compared with the Wishart classifier based on the analysis of the polarimetric coherency matrix only. As our full polarimetric data are also available in P and L bands, this study evaluates the contribution of the different wavelength. This study shown that the combination of SVM and full polarimetric data, associates with different wavelength, gives promising results. Copyright SFPT Numéro de notice : A2006-619 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans En ligne : https://www.isprs.org/proceedings/XXXVI/part1/Papers/T09-39.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28342
in Revue Française de Photogrammétrie et de Télédétection > n° 182 (Juin 2006) . - pp 23 - 27[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 018-06021 RAB Revue Centre de documentation En réserve L003 Disponible Documents numériques
en open access
Classification of fully polarimetric... - pdf editeur ISPRSAdobe Acrobat PDFHigh spatial resolution satellite imagery, DEM derivatives, and image segmentation for the detection of mass wasting processes / J. Barlow in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 6 (June 2006)
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Titre : High spatial resolution satellite imagery, DEM derivatives, and image segmentation for the detection of mass wasting processes Type de document : Article/Communication Auteurs : J. Barlow, Auteur ; Steven E. Franklin, Auteur ; Y. Martin, Auteur Année de publication : 2006 Article en page(s) : pp 687 - 692 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] classification ascendante hiérarchique
[Termes IGN] classification dirigée
[Termes IGN] effondrement de terrain
[Termes IGN] géomorphologie locale
[Termes IGN] image à haute résolution
[Termes IGN] image SPOT 5
[Termes IGN] interprétation automatique
[Termes IGN] modèle numérique de surface
[Termes IGN] réflectance du sol
[Termes IGN] relief
[Termes IGN] segmentation d'imageRésumé : (Auteur) An automated approach to identifying landslides using a combination of high-resolution satellite imagery and digital elevation derivatives is offered as an alternative to aerial photographic interpretation. Previous research has demonstrated that per pixel spectral response patterns are ineffective in discriminating mass movements. This technique utilizes image segmentation and digital elevation data in order to identify mass movements based not only on their reflectance but also on their shape properties and their geomorphic context. Dividing the classification by process into debris slides, debris flows, and rock slides makes the method far more useful than methods that group all mass movements together. A hierarchical classification scheme is utilized to eliminate areas that are not of interest and to identify areas where mass movements are probable. A supervised classification is then conducted using spectral, shape, and textural properties to identify failures that were greater than 1 ha in area. The resulting accuracy was 90 percent for debris slides, 60 percent for debris flows, and 80 percent for rock slides. Copyright ASPRS Numéro de notice : A2006-232 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.72.6.687 En ligne : https://doi.org/10.14358/PERS.72.6.687 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27959
in Photogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 6 (June 2006) . - pp 687 - 692[article]Mapping built-up areas from multitemporal interferometric SAR images: a segment-based approach / Leena Matikainen in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 6 (June 2006)
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Titre : Mapping built-up areas from multitemporal interferometric SAR images: a segment-based approach Type de document : Article/Communication Auteurs : Leena Matikainen, Auteur ; M.E. Engdahl, Auteur ; Juha Hyyppä, Auteur Année de publication : 2006 Article en page(s) : pp 701 - 714 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] cartographie automatique
[Termes IGN] classification dirigée
[Termes IGN] densité du bâti
[Termes IGN] image ERS-SAR
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] interprétation automatique
[Termes IGN] milieu urbain
[Termes IGN] segmentation d'image
[Termes IGN] utilisation du solRésumé : (Auteur) Automatic mapping of built-up areas from a multitemporal interferometric ERS-1/2 Tandem dataset was studied. The image data were segmented into homogeneous regions, and the regions were classified as built-up areas, forests, and open areas using their mean intensity and coherence values and additional contextual information. Compared with a set of reference points, an overall classification accuracy of 97 percent was achieved. The classification process was highly automatic and resulted in homogeneous regions resembling a map drawn by a human interpreter. The feasibility of the imagery for dividing built-up areas further into subclasses was also investigated. The results suggest that low-rise areas, high-rise areas, and industrial areas are difficult to distinguish from each other. On the other hand, a correlation between the building density, the proportion of land covered with buildings, and intensity/coherence in the image data was found. The dataset thus appeared to be promising for classifying built-up areas into subclasses according to building density. Copyright ASPRS Numéro de notice : A2006-233 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.72.6.701 En ligne : https://doi.org/10.14358/PERS.72.6.701 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27960
in Photogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 6 (June 2006) . - pp 701 - 714[article]Multi-image matching for DSM generation from Ikonos imagery / Li Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 60 n° 3 (May 2006)
PermalinkOn the integration of object-based models and field-based models in GIS / K. Kjenstad in International journal of geographical information science IJGIS, vol 20 n° 5 (may 2006)
PermalinkMonitoring active volcanism with the autonomous sciencecraft experiment on EO-1 / A.G. Chien in Remote sensing of environment, vol 101 n° 4 (30/04/2006)
PermalinkAutomatic building detection using the Dempster-Shafer algorithm / Y.H. Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 4 (April 2006)
PermalinkConsideration of smoothing techniques for hyperspectral remote sensing / C. Vaiphasa in ISPRS Journal of photogrammetry and remote sensing, vol 60 n° 2 (April 2006)
PermalinkRelevance of hyperspectral data for natural resources management / T.V. Ramachandra in GIS development, vol 10 n° 4 (April 2006)
PermalinkInterrelationships between spatial resolution and per-pixel classifiers for extracting information classes part 1: the urban environment / J.R. Jensen (29/03/2006)
PermalinkInterrelationships between spatial resolution and per-pixel classifiers for extracting information classes part 2: the natural environment / M.E. Hodgson (29/03/2006)
PermalinkPermalinkDetection of ancient settlement mounds: archaeological survey based on the STRM terrain model / B.H. Menze in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 3 (March 2006)
PermalinkMangrove mapping and monitoring: RS and GIS in conservation and management planning / S.K. Singh in GIM international, vol 20 n° 3 (March 2006)
PermalinkRoad extraction based on fuzzy logic and mathematical morphology from pan-sharpened Ikonos images / Ali Mohammadzadeh in Photogrammetric record, vol 21 n° 113 (March - May 2006)
PermalinkContextual reconstruction of cloud-contaminated multitemporal multispectral image / F. Melgani in IEEE Transactions on geoscience and remote sensing, vol 44 n° 2 (February 2006)
PermalinkA new approach to the nearest-neighbour method to discover cluster features in overlaid spatial point processes / Tao Pei in International journal of geographical information science IJGIS, vol 20 n° 2 (february 2006)
PermalinkNoise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage / H. Othman in IEEE Transactions on geoscience and remote sensing, vol 44 n° 2 (February 2006)
PermalinkParcel-based classification / J. Wijnant in GEO: Geoconnexion international, vol 5 n° 2 (february 2006)
PermalinkPermalinkAnalyse et évaluation de l'érosion hydrique et du ravinement associé dans la ville de Nioro-du-Rip (Sénégal) par télédétection et SIG / B. Ndoye (2006)
PermalinkBadly posed classification of remotely sensed images : an experimental comparison of existing data labeling systems / A. Baraldi in IEEE Transactions on geoscience and remote sensing, vol 44 n° 1 (January 2006)
PermalinkCAp 2006, 8e conférence francophone sur l'apprentissage automatique, 22 - 24 mai 2006, Trégastel, France / Laurent Miclet (2006)
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