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Multitemporel fuzzy classification model based on class transition possibilities / G.L.A. Mota in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 3 (August 2007)
[article]
Titre : Multitemporel fuzzy classification model based on class transition possibilities Type de document : Article/Communication Auteurs : G.L.A. Mota, Auteur ; R. Feitosa, Auteur ; H.L.C. Coutinho, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 186 - 200 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme génétique
[Termes IGN] Brésil
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification floue
[Termes IGN] image Landsat
[Termes IGN] image multitemporelle
[Termes IGN] modélisation spatialeRésumé : (Auteur) This paper proposes a new method to model temporal knowledge and to combine it with spectral and spatial knowledge within an integrated fuzzy automatic image classification framework for land-use land-cover map update applications. The classification model explores not only the object features, but also information about its class at a previous date. The method expresses temporal class dependencies by means of a transition diagram, assigning a possibility value to each class transition. A Genetic Algorithm (GA) carries out the class transition possibilities estimation. Temporal and spectral/spatial classification results are combined by means of fuzzy aggregation. The improvement achieved by the use of multitemporal knowledge rather than a pure monotemporal approach was assessed in a real application using LANDSAT images from Midwest Brazil. The experiments showed that the use of temporal knowledge markedly improved the classification performance, in comparison to a conventional single-time classification. A further observation was that multitemporal knowledge may subsume the knowledge related to steady spatial attributes whose values do not significantly change over time. Copyright ISPRS Numéro de notice : A2007-368 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2007.04.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2007.04.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28731
in ISPRS Journal of photogrammetry and remote sensing > vol 62 n° 3 (August 2007) . - pp 186 - 200[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-07051 SL Revue Centre de documentation Revues en salle Disponible Rule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping / Robert Lucas in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 3 (August 2007)
[article]
Titre : Rule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping Type de document : Article/Communication Auteurs : Robert Lucas, Auteur ; A. Rowlands, Auteur ; A. Brown, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 165 - 185 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] agriculture
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification floue
[Termes IGN] eCognition
[Termes IGN] habitat (urbanisme)
[Termes IGN] image Landsat
[Termes IGN] image multitemporelle
[Termes IGN] indice de végétation
[Termes IGN] intelligence artificielle
[Termes IGN] logique floue
[Termes IGN] Pays de Galles
[Termes IGN] segmentation d'image
[Termes IGN] série temporelleRésumé : (Auteur) The aim is to evaluate the use of time-series of Landsat sensor data acquired over an annual cycle for mapping semi-natural habitats and agricultural land cover. The location is Berwyn Mountains, North Wales, United Kingdom. The methods are Using eCognition Expert, segmentation of the Landsat sensor data was undertaken for actively managed agricultural land based on Integrated Administration and Control System (IACS) land parcel boundaries, whilst a per-pixel level segmentation was undertaken for all remaining areas. Numerical decision rules based on fuzzy logic that coupled knowledge of ecology and the information content of single and multi-date remotely sensed data and derived products (e.g., vegetation indices) were developed to discriminate vegetation types based primarily on inferred differences in phenology, structure, wetness and productivity. The results : The rule-based classification gave a good representation of the distribution of habitats and agricultural land. The more extensive, contiguous and homogeneous habitats could be mapped with accuracies exceeding 80%, although accuracies were lower for more complex environments (e.g., upland mosaics) or those with broad definition (e.g., semi-improved grasslands). The application of a rule-based classification to temporal imagery acquired over selected periods within an annual cycle provides a viable approach for mapping and monitoring of habitats and agricultural land in the United Kingdom that could be employed operationally. Copyright ISPRS Numéro de notice : A2007-367 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2007.03.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2007.03.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28730
in ISPRS Journal of photogrammetry and remote sensing > vol 62 n° 3 (August 2007) . - pp 165 - 185[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-07051 SL Revue Centre de documentation Revues en salle Disponible Satellite image classification using granular neural networks / D. Stathakis in International Journal of Remote Sensing IJRS, vol 27 n°18 - 19 - 20 (October 2006)
[article]
Titre : Satellite image classification using granular neural networks Type de document : Article/Communication Auteurs : D. Stathakis, Auteur ; A. Vasilakos, Auteur Année de publication : 2006 Article en page(s) : pp 3991 - 4003 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] classification floue
[Termes IGN] classification par réseau neuronal
[Termes IGN] granularité d'image
[Termes IGN] image IRS-LISSRésumé : (Auteur) The increased synergy between neural networks (NN) and fuzzy sets has led to the introduction of granular neural networks (GNNs) that operate on granules of information, rather than information itself. The fact that processing is done on a conceptual rather than on a numerical level, combined with the representation of granules using linguistic terms, results in increased interpretability. This is the actual benefit, and not increased accuracy, gained by GNNs. The constraints used to implement the GNN are such that accuracy degradation should not be surprising. Having said that, it is well known that simple structured NNs tend to be less prone to over-fitting the training data set, maintaining the ability to generalize and more accurately classify previously unseen data. Standard NNs are frequently found to be accurate but difficult to explain, hence they are often associated with the black box syndrome. Because in GNNs the operation is carried out at a conceptual level, the components have unambiguous meaning, revealing how classification decisions are formed. In this paper, the interpretability of GNNs is exploited using a satellite image classification problem. We examine how land use classification using both spectral and non-spectral information is expressed in GNN terms. One further contribution of this paper is the use of specific symbolization of the network components to easily establish causality relationships. Copyright Taylor & Francis Numéro de notice : A2006-460 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600567779 En ligne : https://doi.org/10.1080/01431160600567779 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28184
in International Journal of Remote Sensing IJRS > vol 27 n°18 - 19 - 20 (October 2006) . - pp 3991 - 4003[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-06101 RAB Revue Centre de documentation En réserve L003 Disponible Comparison 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)
[article]
Titre : Comparison of computational intelligence based classification techniques for remotely sensed optical image classification Type de document : Article/Communication Auteurs : D. Stathakis, Auteur ; A. Vasilakos, Auteur Année de publication : 2006 Article en page(s) : pp 2305 - 2318 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] analyse comparative
[Termes IGN] classification dirigée
[Termes IGN] classification floue
[Termes IGN] classification par algorithme génétique
[Termes IGN] classification par réseau neuronal
[Termes IGN] image optique
[Termes IGN] occupation du solRésumé : (Auteur) Several computational intelligence components, namely neural networks (NNs), fuzzy sets, and genetic algorithms (GAs), have been applied separately or in combination to the process of remotely sensed data classification. By applying computational intelligence, we expect increased accuracy through the use of NNs, optimal NN structure and parameter determination via GAs, and transparency using fuzzy sets is expected. This paper systematically reviews and compares several configurations in the particular context of remote sensing for land cover. In addition, some of the configurations used here, such as NEFCASS and CANFIS, have few previous applications in the field. A comparison of the configurations is achieved by testing the different methods with exactly the same case-study data. A thorough assessment of results is performed by constructing an accuracy matrix for each training and testing data set. The evaluation of different methods is not only based on accuracy but also on compactness, completeness, and consistency. The architecture, produced rule set, and training parameters for the specific classification task are presented. Some comments and directions for future work are given. Copyright IEEE Numéro de notice : A2006-397 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2006.872903 En ligne : https://doi.org/10.1109/TGRS.2006.872903 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28121
in IEEE Transactions on geoscience and remote sensing > vol 44 n° 8 (August 2006) . - pp 2305 - 2318[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-06081 RAB Revue Centre de documentation En réserve L003 Disponible Fuzzy classification: a case study using Landsat TM images in Iran / A.M. Lak in GIM international, vol 20 n° 7 (July 2006)
[article]
Titre : Fuzzy classification: a case study using Landsat TM images in Iran Type de document : Article/Communication Auteurs : A.M. Lak, Auteur ; M. Hamrah, Auteur ; G.H. Majdabadi, Auteur Année de publication : 2006 Article en page(s) : pp 42 - 43 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] classification barycentrique
[Termes IGN] classification floue
[Termes IGN] classification hybride
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] distribution de Gauss
[Termes IGN] image Landsat-TM
[Termes IGN] Iran
[Termes IGN] MatlabRésumé : (Editeur) Extraction of information from satellite images is a solution for countries without up-to-date base maps. Such images can be easily obtained and cover vast areas. Information is mostly extracted using multispectral classification, but many methods have been developed. The authors examined 'fuzzy classification' and found it more accurate and requiring less computing time than other methods. Copyright GITC Numéro de notice : A2006-253 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27980
in GIM international > vol 20 n° 7 (July 2006) . - pp 42 - 43[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 061-06071 RAB Revue Centre de documentation Revues en salle Disponible On possible measures for evaluating the degree of uncertainty of fuzzy thematic maps / C. Ricotta in International Journal of Remote Sensing IJRS, vol 26 n° 24 (December 2005)PermalinkIntegrating high resolution remote sensing, GIS and fuzzy set theory for identifying susceptibility areas of forest insect infestations / C. Bone in International Journal of Remote Sensing IJRS, vol 26 n° 21 (November 2005)PermalinkSnow cover monitoring in Alpine regions using ENVISAT optical data / M. Pepe in International Journal of Remote Sensing IJRS, vol 26 n° 21 (November 2005)PermalinkComparison of land cover maps using fuzzy agreement / Steffen Fritz 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)PermalinkDesigning fuzzy rule based classifier using self-organizing feature map for analysis of multispectral satellite images / Nikhil R. Pal in International Journal of Remote Sensing IJRS, vol 26 n° 10 (May 2005)PermalinkLand 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)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)PermalinkAlternative representations of in-stream habitat: classification using remote sensing, hydraulic modelling, and fuzzy logic / C. Legleiter in International journal of geographical information science IJGIS, vol 19 n° 1 (january 2005)PermalinkInteractive and visual fuzzy classification of remotely sensed imagery for exploration of uncertainty / Arko Lucieer in International journal of geographical information science IJGIS, vol 18 n° 5 (august 2004)PermalinkAreas of fuzzy geographical entities / Cidália Costa Fonte in International journal of geographical information science IJGIS, vol 18 n° 2 (march 2004)PermalinkA double continuous approach to visualization and analysis of categorial maps / T. Hengl in International journal of geographical information science IJGIS, vol 18 n° 2 (march 2004)PermalinkMulti-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information / U.C. Benz in ISPRS Journal of photogrammetry and remote sensing, vol 58 n° 3-4 (January - June 2004)PermalinkLinear features extraction in rain forest context from interferometric SAR images by fusion of coherence and amplitude information / V.P. Onana in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)PermalinkA combined fuzzy pixel-based and object-based approach for classification of high-resolution multispectral data over urban areas / A.K. Shackelford in IEEE Transactions on geoscience and remote sensing, vol 41 n° 10 (October 2003)PermalinkMultitemporal/multiband SAR classification of urban areas using spatial analysis: statistical versus neural kernel-based approach / T. Macri Pellizzei in IEEE Transactions on geoscience and remote sensing, vol 41 n° 10 (October 2003)PermalinkA hierarchical fuzzy classification approach for high-resolution multispectral data over urban areas / A.K. Shackelford in IEEE Transactions on geoscience and remote sensing, vol 41 n° 9 (September 2003)PermalinkImprovements to urban area characterization using multitemporal and multiangle SAR images / F. Dell'acqua in IEEE Transactions on geoscience and remote sensing, vol 41 n° 9 (September 2003)PermalinkThe use of fully polarimetric information for the fuzzy neural classification of SAR images / C.T. Chen in IEEE Transactions on geoscience and remote sensing, vol 41 n° 9 (September 2003)PermalinkRough and fuzzy geographical data integration / K. Oukbir in International journal of geographical information science IJGIS, vol 17 n° 3 (may 2003)PermalinkPermalinkStatistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutions / Robert Gilmore Pontius in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 10 (October 2002)PermalinkA comparison of fuzzy vs. augmented-ISODATA classification algorithms for cloud-shadow discrimination from Landsat images / A.M. Melesse in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 9 (September 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)PermalinkDetection of urban structures in SAR images by robust fuzzy clustering algorithms: the example of street tracking / F. Dell'acqua in IEEE Transactions on geoscience and remote sensing, vol 39 n° 10 (October 2001)PermalinkCartogenèse numérique des types de sols et de leurs incertitudes par la combinaison de corrélations sur les facteurs environnementaux et des géostatistiques : application aux sols des environs de La Rochelle / F. Carre in Photo interprétation, vol 38 n° 3-4 (Septembre 2000)PermalinkAdvanced polarimetric SAR data classification for cartographic information extraction / Manfred F. Buchroithner (31/05/1999)PermalinkAdvances in remote sensing and GIS analysis, [selected papers from a meeting held at the University of Southampton, July 25, 1996] / P.M. Atkinson (1999)PermalinkRSS 99 Earth observation / P. Pan (1999)PermalinkCartographie semi-automatique de l'évolution de l'occupation des sols par télédétection / Hervé Le Men (1996)PermalinkPermalinkCloud classification from satellite data using a fuzzy sets algorithm: a polar example / J.R. Key in International Journal of Remote Sensing IJRS, vol 10 n° 12 (December 1989)Permalink