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Multispectral image classification: a supervised neural computation approach based on rough-fuzzy membership function and weak fuzzy similarity relation / A. Agrawal in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)
[article]
Titre : Multispectral image classification: a supervised neural computation approach based on rough-fuzzy membership function and weak fuzzy similarity relation Type de document : Article/Communication Auteurs : A. Agrawal, Auteur ; N. Kumar, Auteur ; M. Radhakrishna, Auteur Année de publication : 2007 Article en page(s) : pp 4597 - 4608 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] ERDAS Imagine
[Termes IGN] image IRS-LISS
[Termes IGN] image multibande
[Termes IGN] incertitude des données
[Termes IGN] Inde
[Termes IGN] Kappa de Cohen
[Termes IGN] Perceptron multicouche
[Termes IGN] sous ensemble flouRésumé : (Auteur) A supervised neural network classification model based on rough-fuzzy membership function, weak fuzzy similarity relation, multilayer perceptron, and back-propagation algorithm is proposed. The described model is capable of dealing with rough uncertainty as well as fuzzy uncertainty associated with the classification of multispectral images. The concept of weak fuzzy similarity relation is used for generation of fuzzy equivalence classes during the calculation of rough-fuzzy membership function. The model allows efficient modelling of indiscernibility and fuzziness between patterns by appropriate weights being assigned using the back-propagated errors depending upon the rough-fuzzy membership values at the corresponding outputs. The effectiveness of the proposed model is demonstrated on classification problem of IRS-P6 LISS IV image of Allahabad area. The results are compared with statistical (minimum distance to means), conventional Multi-Layer Perceptron (MLP) and Fuzzy Multi-Layer Perceptron (FMLP) models. The better overall accuracy, user's and producer's accuracies and kappa coefficient of the proposed classifier in comparison to other considered models demonstrate the effectiveness of this model in multispectral image classification. Copyright Taylor & Francis Numéro de notice : A2007-449 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701244898 En ligne : https://doi.org/10.1080/01431160701244898 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28812
in International Journal of Remote Sensing IJRS > vol 28 n°19-20 (October 2007) . - pp 4597 - 4608[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-07111 RAB Revue Centre de documentation En réserve L003 Disponible Characterizing patterns of plant distribution in a southern California salt marsh using remotely sensed topographic and hyperspectral data and local tidal fluctuations / S. Sadro in Remote sensing of environment, vol 110 n° 2 (28/09/2007)
[article]
Titre : Characterizing patterns of plant distribution in a southern California salt marsh using remotely sensed topographic and hyperspectral data and local tidal fluctuations Type de document : Article/Communication Auteurs : S. Sadro, Auteur ; M. Gastil-Buhl, Auteur ; J. Melack, Auteur Année de publication : 2007 Article en page(s) : pp 226 - 239 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] couvert végétal
[Termes IGN] distribution spatiale
[Termes IGN] données lidar
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] marais salé
[Termes IGN] marée océanique
[Termes IGN] modèle numérique de surfaceRésumé : (Auteur) We used LiDAR topographic data, AVIRIS hyperspectral data, and locally measured tidal fluctuations to characterize patterns of plant distribution within a southern California salt marsh (Carpinteria Salt Marsh (CSM)). LiDAR data required ground truthing and correction before they were suitable for use. Twenty to forty percent of the uncertainty associated with LiDAR was due to variance in the elevation of the target surface, the balance was attributed to error inherent in the LiDAR system. The incidence of LiDAR penetration of plant canopy cover (i.e., registration of ground elevation) was only three percent. The depth of LiDAR penetration into the plant canopy varied according to plant species composition; plant species-specific corrections significantly improved LiDAR accuracy (58% reduction in overall uncertainty) and with the use of ground-based surveys, reduced overall RMSE to an average of 6.3 cm in vegetated areas. A supervised classification of AVIRIS data was used to generate a vegetation map with six classification types; overall classification accuracy averaged 59% with a kappa coefficient of 0.40. The vegetation classification map was overlaid with a LiDAR-based digital elevation model (DEM) to compute elevation distributions and frequencies of tidal inundation. The average elevations of the dominant plant classifications found in CSM (e.g., Salicornia virginica, Jaumea carnosa, and salt-grass mix, a mixture of multiple marsh plant species) occurred within a 17 cm range, a vertical change that resulted in a 7% difference in the period of tidal inundation. Numéro de notice : A2007-150 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2007.02.024 En ligne : https://doi.org/10.1016/j.rse.2007.02.024 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28513
in Remote sensing of environment > vol 110 n° 2 (28/09/2007) . - pp 226 - 239[article]Détection des haies et segmentation automatique / A. Dommanget in Géomatique expert, n° 57 (01/07/2007)
[article]
Titre : Détection des haies et segmentation automatique Type de document : Article/Communication Auteurs : A. Dommanget, Auteur ; C. Barnerias, Auteur Année de publication : 2007 Article en page(s) : pp 56 - 63 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] ArcView
[Termes IGN] classification barycentrique
[Termes IGN] classification dirigée
[Termes IGN] échelle cartographique
[Termes IGN] erreur de classification
[Termes IGN] forêt
[Termes IGN] haie
[Termes IGN] Ille-et-Vilaine (35)
[Termes IGN] indice de végétation
[Termes IGN] inventaire de la végétation
[Termes IGN] logiciel de traitement d'image
[Termes IGN] logique floue
[Termes IGN] orthophotographie
[Termes IGN] photographie aérienne
[Termes IGN] photographie infrarouge couleur
[Termes IGN] projection conique conforme de Lambert
[Termes IGN] segmentation d'imageRésumé : (Auteur) L'objet de la présente étude était d'extraire automatiquement les haies à partir d'orthophotographies infrarouge couleurs que l'IFN possède. Etant donné le champ de compétences de l'IFN, nous nous sommes intéressés également à l'identification des forêts. Ce travail s'inspire largement de la contribution d'Alban Dommanget réalisée dans le cadre d'un stage de MASTER 2 "Système d'Informations Géographiques" de l'Université de Caen au sein de l'Inventaire Forestier National (IFN). Copyright CiMax Numéro de notice : A2007-334 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28697
in Géomatique expert > n° 57 (01/07/2007) . - pp 56 - 63[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 265-07041 RAB Revue Centre de documentation En réserve L003 Disponible Mapping of salt-affected soils using TM images / P. Garcia Rodriguez in International Journal of Remote Sensing IJRS, vol 28 n°11-12 (June 2007)
[article]
Titre : Mapping of salt-affected soils using TM images Type de document : Article/Communication Auteurs : P. Garcia Rodriguez, Auteur ; M.E. Perrez Gonzales, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 2713 - 2722 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Castille-La Manche
[Termes IGN] classification dirigée
[Termes IGN] déformation de surface
[Termes IGN] eau souterraine
[Termes IGN] image Landsat-TM
[Termes IGN] inondation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] risque naturel
[Termes IGN] sédiment
[Termes IGN] sol salinRésumé : (Auteur) Landsat images supply significant information on the different aspects of the physical environment necessary to determine the distribution of salty soils. This work centres on the La Mancha area (Central Spain) which, due to its flat topography, exhibits ideal conditions to show surface and groundwater movement, as well as sediment distribution. Combination of these factors is essential for development. The main goal of this study is to derive information on the distribution of salt-affected soils, as well as the area subject to flood risk. Multitemporal Landsat TM images selected from the 1990s have been used for this purpose. TM images are useful for delineation of mesozoic sediments rich in salts and/or areas with high humidity content. These images have been geo-referenced to the UTM coordinate system and have been digitally enhanced. Principal components, NDVI and supervised classification were computed. Therefore, it is quite possible to predict with a high degree of probability the development of saline soils, but their precise classification is not always possible, owing to the fact that they are usually associated with other soil groups: calcisols, regosols, luvisols and kastanozems. Salt-affected soils have been found to be associated with clayish mesozoic sediments, hollows, flood plain area and subsurface and groundwater movements. Complementary fieldwork is necessary in order to confirm digital values. Copyright Taylor & Francis Numéro de notice : A2007-310 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600928658 En ligne : https://doi.org/10.1080/01431160600928658 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28673
in International Journal of Remote Sensing IJRS > vol 28 n°11-12 (June 2007) . - pp 2713 - 2722[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-07071 RAB Revue Centre de documentation En réserve L003 Disponible Improving land-cover classification using recognition threshold neural networks / M.J. Aitkenhead in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 4 (April 2007)
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Titre : Improving land-cover classification using recognition threshold neural networks Type de document : Article/Communication Auteurs : M.J. Aitkenhead, Auteur ; R. Dyer, Auteur Année de publication : 2007 Article en page(s) : pp 413 - 421 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] image Landsat
[Termes IGN] Philippines
[Termes IGN] seuillage d'image
[Termes IGN] surface cultivéeRésumé : (Auteur) The use of neural networks to classify land-cover from remote sensing imagery relies on the ability to determine a winner from the candidate land-cover types based on the imagery information available. In the case of a “winner- takes-all” scenario, this does not allow us a measure of how much the prediction of each pixel’s land-cover can be trusted. We present a three-stage method where only winning candidates which are given a clear lead over the other land-cover types are accepted, with a neighborhood relationship and the application of mixed pixels being used to provide full classification. This method allows us to place more faith in the resulting map than simply taking the winner, and results in a higher accuracy of classification. The method is applied to Landsat imagery of an area of the Philippines where natural, urban, and cultivated land-cover types exist. Copyright ASPRS Numéro de notice : A2007-143 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.4.413 En ligne : https://doi.org/10.14358/PERS.73.4.413 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28506
in Photogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 4 (April 2007) . - pp 413 - 421[article]An operational MISR pixel classifier using support vector machines / D. Mazzoni in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)PermalinkComparison between several feature extraction/classification methods for mapping complicated agricultural land use patches using airborne hyperspectral data / S. Lu in International Journal of Remote Sensing IJRS, vol 28 n°5-6 (March 2007)PermalinkFeature extractions for small sample size classification problem / B.C. Kuo in IEEE Transactions on geoscience and remote sensing, vol 45 n° 3 (March 2007)PermalinkOil spill detection in Radarsat and Envisat SAR images / A.H. Solberg in IEEE Transactions on geoscience and remote sensing, vol 45 n° 3 (March 2007)PermalinkTerrestrial and submerged aquatic vegetation mapping in Fire Island national seashore using high spatial resolution remote sensing data / Y. Wang in Marine geodesy, vol 30 n° 1-2 (March - June 2007)PermalinkGeneration of geometrically and radiometrically terrain corrected SAR image products / A. Loew in Remote sensing of environment, vol 106 n° 3 (15/02/2007)PermalinkExtraction of spectral channels from hyperspectral images for classification purposes / S.B. Serpico in IEEE Transactions on geoscience and remote sensing, vol 45 n° 2 (February 2007)PermalinkAssessing the effect of attribute uncertainty on the robustness of choropleth map classification / N. Xiao in International journal of geographical information science IJGIS, vol 21 n° 1-2 (january 2007)PermalinkAuto-qualification de données géographiques 3D par appariement multi-image et classification supervisée / Laurence Boudet (2007)PermalinkDétection des zones débroussaillées dans les images simulées ORFEO / Marie-Cécile Lyx (2007)PermalinkEvolution des habitats dans les montagnes d'Araucania / Rémi Pas (2007)PermalinkSeparating the weeds from the trees / M. Norris-Rogers in GIM international, vol 21 n° 1 (January 2007)PermalinkApport des données Spot et Landsat au suivi des inondations dans l'estuaire du fleuve Sénégal / A.M. Dia in Photo interprétation, vol 42 n° 4 (Décembre 2006)PermalinkComparison and integration of radar and optical data for land use / cover mapping / Nathaniel D. Herold in Geocarto international, vol 21 n° 4 (December 2006 - February 2007)PermalinkMapping salt-marsh vegetation by multispectral and hyperspectral remote sensing / E. Belluco in Remote sensing of environment, vol 105 n° 1 (15/11/2006)PermalinkOn comparing multifractal and classical features in minimum distance classification of AVHRR imagery / T. Parrinello in International Journal of Remote Sensing IJRS, vol 27 n°18 - 19 - 20 (October 2006)PermalinkA pixel shape index coupled with spectral information for classification of high spatial resolution remotely sensed imagery / L. Zhang in IEEE Transactions on geoscience and remote sensing, vol 44 n° 10 Tome 2 (October 2006)PermalinkTraining set size requirements for the classification of a specific class / Giles M. Foody in Remote sensing of environment, vol 104 n° 1 (15/09/2006)PermalinkComparison of computational intelligence based classification techniques for remotely sensed optical image classification / D. Stathakis in IEEE Transactions on geoscience and remote sensing, vol 44 n° 8 (August 2006)PermalinkError assessment in two lidar-derived TIN datasets / M.H. Peng in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 8 (August 2006)PermalinkA patch-based image classification by integrating hyperspectral data with GIS / B. Zhang in International Journal of Remote Sensing IJRS, vol 27 n°15-16 (August 2006)PermalinkSome issues in the classification of DAIS hyperspectral data / M. Pal in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)PermalinkStudy of tectonics in relation to the seismic activity of the Davalt area, Nasik district, Maharashtra, India using remote sensing and GIS techniques / J. Sarup in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)PermalinkUrban land-use classification using variogram-based analysis with an aerial photograph / S.S. Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 7 (July 2006)PermalinkApport 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)PermalinkHigh 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)PermalinkMapping 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)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)PermalinkMangrove mapping and monitoring: RS and GIS in conservation and management planning / S.K. Singh in GIM international, vol 20 n° 3 (March 2006)PermalinkAnalyse 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)PermalinkEtude de différents facteurs influant les classifications d'images multi-résolution / F. Kazemipour (2006)PermalinkA supervised classification approach towards quality self-diagnosis of 3D building models using digital aerial imagery / Laurence Boudet (2006)PermalinkPermalinkIntegrating LIDAR elevation data, multi-spectral imagery and neural network modelling for marsh characterization / J.T. Morris in International Journal of Remote Sensing IJRS, vol 26 n° 23 (December 2005)PermalinkReconstructing spatiotemporal trajectories from sparse data / P. Partsinevelos in ISPRS Journal of photogrammetry and remote sensing, vol 60 n° 1 (December 2005 - March 2006)PermalinkSupervised image classification by contextual adaboost based on posteriors in neighborhoods / Ryuei Nishii in IEEE Transactions on geoscience and remote sensing, vol 43 n° 11 (November 2005)PermalinkLAI retrieval from multiangular image classification and inversion of a ray tracing model / R. Casa in Remote sensing of environment, vol 98 n° 4 (30/10/2005)PermalinkFusion of hyperspectral data using segmented PCT for color representation and classification / V. Tsagaris in IEEE Transactions on geoscience and remote sensing, vol 43 n° 10 (October 2005)PermalinkSpectral filtering and classification of terrestrial laser scanner point clouds / Derek D. Lichti in Photogrammetric record, vol 20 n° 111 (September - November 2005)PermalinkFurther developments of a fuzzy set map comparison approach / Alex Hagen-Zanker in International journal of geographical information science IJGIS, vol 19 n° 7 (august 2005)PermalinkEstimating and accommodating uncertainty through the soft classification of remote sensing data / M.A. Ibrahim in International Journal of Remote Sensing IJRS, vol 26 n° 14 (July 2005)PermalinkSpatial knowledge databases as applied to the detection of changes in urban land use / T.Y. Chou in International Journal of Remote Sensing IJRS, vol 26 n° 14 (July 2005)PermalinkSuper-resolution land cover mapping using a Markov random field based approach / T. Kasetkasem in Remote sensing of environment, vol 96 n° 3 (30/06/2005)Permalink