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A neural network image interpretation system to extract rural and urban land use and land cover information from remote sensor data / J.R. Jensen in Geocarto international, vol 16 n° 1 (March - May 2001)
[article]
Titre : A neural network image interpretation system to extract rural and urban land use and land cover information from remote sensor data Type de document : Article/Communication Auteurs : J.R. Jensen, Auteur ; F. Qiu, Auteur ; K. Patterson, Auteur Année de publication : 2001 Article en page(s) : pp 19 - 28 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photo-interprétation
[Termes IGN] image Ikonos
[Termes IGN] occupation du sol
[Termes IGN] photo-interprétation
[Termes IGN] réseau neuronal artificiel
[Termes IGN] utilisation du solRésumé : (Auteur) This paper describes the characteristics of a neural network image interpretation system that is designed to extract both rural land cover and urban land use from high spatial resolution imagery (e.g., digitized aerial photography, IKONOS imagery) and/or from relatively coarse spatial and spectral resolution remote sensor data (e.g., Landsat Thematic Mapper). The system consists of modules that a) classify remote sensing imagery into different land use/land cover types, b) segment the rural land cover information into relatively homogeneous polygons in a standard GISformat, and/or c) digitize and interpret urban/suburban land use cover polygons based on their feature attribute information with the aid of a neural network. Numéro de notice : A2001-044 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040108542179 En ligne : https://doi.org/10.1080/10106040108542179 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21746
in Geocarto international > vol 16 n° 1 (March - May 2001) . - pp 19 - 28[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-01011 RAB Revue Centre de documentation En réserve L003 Disponible GeoComputational modelling / Manfred M. Fischer (2001)
Titre : GeoComputational modelling : techniques and applications Type de document : Monographie Auteurs : Manfred M. Fischer, Éditeur scientifique ; Yee Leung, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2001 Collection : Advances in spatial science, ISSN 1430-9602 Importance : 275 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-540-41968-6 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatiale
[Termes IGN] classification
[Termes IGN] classification par réseau neuronal
[Termes IGN] image multibande
[Termes IGN] modélisation
[Termes IGN] réseau neuronal artificiel
[Termes IGN] traitement d'image
[Termes IGN] urbanisationNuméro de notice : 18559 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Monographie Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=55428 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 18559-01 37.20 Livre Centre de documentation Géomatique Disponible Spatial prediction of fire ignition probabilities: comparing logistic regression and neural networks / M.J. Perestrello De Vasconcelos in Photogrammetric Engineering & Remote Sensing, PERS, vol 67 n° 1 (January 2001)
[article]
Titre : Spatial prediction of fire ignition probabilities: comparing logistic regression and neural networks Type de document : Article/Communication Auteurs : M.J. Perestrello De Vasconcelos, Auteur ; S. Silva, Auteur ; Margarida Tomé, Auteur ; M. Alvim, Auteur ; J.M. Cardoso Pereira, Auteur Année de publication : 2001 Article en page(s) : pp 73 - 81 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] analyse spatiale
[Termes IGN] cartographie des risques
[Termes IGN] incendie de forêt
[Termes IGN] modélisation
[Termes IGN] Portugal
[Termes IGN] prévention des risques
[Termes IGN] prévision
[Termes IGN] réseau neuronal artificiel
[Termes IGN] risque naturel
[Termes IGN] système d'information géographiqueRésumé : (Auteur) The objective of this work was to develop and validate models to predict spatially distributed probabilities of ignition of wildland fires in central Portugal. The models were constructed by exploring relationships between ignition location/cause and values of geographical and environmental variables using logistic regression and neural networks. The conclusions are that the spatial patterns of fire ignition identified can be used for prediction, the spatial patterns are different for the different causes, the logistic models and the neural networks both reveal acceptable levels of predictive ability but the neural networks present better accuracy and robustness, the maps produced by the two methods are similar, and the information contained in the spatial position of ignition events can be used to gain predictive capability over an important phenomenon that is difficult to characterize and, for that reason, has not been included in most of the currently used fire danger estimation systems. Numéro de notice : A2001-084 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE/INFORMATIQUE Nature : Article DOI : sans En ligne : https://www.asprs.org/wp-content/uploads/pers/2001journal/january/2001_jan_73-81 [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21784
in Photogrammetric Engineering & Remote Sensing, PERS > vol 67 n° 1 (January 2001) . - pp 73 - 81[article]Advanced polarimetric SAR data classification for cartographic information extraction / Manfred F. Buchroithner (31/05/1999)
contenu dans Remote sensing in the 21st century : economic and environmental applications / José Luis Casanova (2000)
Titre : Advanced polarimetric SAR data classification for cartographic information extraction Type de document : Article/Communication Auteurs : Manfred F. Buchroithner, Auteur ; E. Kraetzschmar, Auteur ; M. Hellmann, Auteur Editeur : Lisse et Amsterdam : Balkema (August Aimé) Année de publication : 31/05/1999 Conférence : EARSeL 1999, 19th symposium, Remote sensing in the 21st century : economic and environmental applications 31/05/1999 02/06/1999 Valladolid Espagne Importance : pp 533 - 539 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
[Termes IGN] classification floue
[Termes IGN] extraction automatique
[Termes IGN] image radar
[Termes IGN] image SIR-C-X-SAR
[Termes IGN] réseau neuronal artificiel
[Termes IGN] valeur propreRésumé : (Auteur) Within the last decade several studies using polarimetric SAR data for bio-/geo-physical feature extraction have been reported and have significantly improved the understanding of polarimetric scattering mechanisms. In a comparative view, the approach presented here, which is based on Shane Cloud's Decomposition Theorem, seems to be most promising : the Entropy H and Angle Classification has been extended by using not only the parameters H and but also the first eigenvalue1. A big advantage of this approach is the high correlation between its results and the physical properties of different landsurface materials, which makes this recently adapted method well-suited for both supervised and automated landcover classification. It is also most useful for the derivation of topographic as well as thematic map information, the scale naturally depending on the sensor's spatial resolution. The well-known DLR Oberpfaffenhofen study site in southern Germany served as a testbed for the exploitation of spaceborne SIR-C/X-SAR data and of L-band data from DLR's airborne experimental ESAR. For validation purposes the classification results have been high-precision geocoded and compared to both ground truth and recent map data, also superimposing the digital national topographic geodata of Germany, ATKIS. The classification proved to be of extraordinary accuracy, as far as can be judged by visual inspection. An exact quantification is underway. The approach presented is being further developed and will - in contrast to the flat test-site used so far - be applied to data flown by a new airborne SAR sensor over mountainous terrain at the northern rim of the Bavarian Alps. First results in this respect look very promising. Numéro de notice : C1999-051 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Communication Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=65817 Beschreibung von Deformationsprozessen durch Volterra- und Fuzzy-Modelle sowie neuronale Netze / K. Heine (1999)
Titre : Beschreibung von Deformationsprozessen durch Volterra- und Fuzzy-Modelle sowie neuronale Netze Titre original : [Description du processus de déformation au travers du modèle Volterra et de la logique floue comme les réseaux neuronaux] Type de document : Thèse/HDR Auteurs : K. Heine, Auteur Editeur : Munich : Bayerische Akademie der Wissenschaften Année de publication : 1999 Collection : DGK - C Sous-collection : Dissertationen num. 516 Importance : 111 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-3-7696-9554-0 Note générale : Bibliographie Langues : Allemand (ger) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] Déformation
[Termes IGN] logique floue
[Termes IGN] modèle de déformation tectonique
[Termes IGN] réseau neuronal artificielIndex. décimale : 30.40 Géodésie physique Résumé : (Auteur) The analysis of the cause-effect-relation of deformation processes is possible by input-output-models on condition that time series of the acting forces and the deformation are available. The description of the process can be realised as well by classical methods like the VOLTERRA-model as by Artificial Neural Networks and Fuzzy models which lately became more and more important in system analysis. The modelling of the deformation process should be comprehended as an process orientated by the objective of the description. That means that the suitability of the several modelling methods for a specific deformation process is to be examined and should the occasion arise a combination of the several methods leeds to an optimised model considering the modelling objective. Numéro de notice : 57782 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Thèse étrangère Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=60273 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 57782-01 30.40 Livre Centre de documentation Géodésie Disponible Conférence d'apprentissage 99, actes de CAP'99, Ecole Polytechnique, Palaiseau, 15-18 juin 1999 / Michèle Sebag (1999)PermalinkThe ASTER polar cloud mask / A.M. Logar in IEEE Transactions on geoscience and remote sensing, vol 36 n° 4 (July 1998)PermalinkUsing genetic learning neural networks for spatial decision making in GIS / J. Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 62 n° 11 (november 1996)PermalinkProceedings of the second workshop Application of artificial intelligence techniques in seismology and engineering seismology / M. Garcia-Fernandez (1996)PermalinkTélédétection aérospatiale / Jules Wilmet (1996)PermalinkArtificial intelligence / Stuart J. Russell (1995)PermalinkCours d'informatique du professeur Bouillé / François Bouillé (1995)PermalinkProceedings of the workshop Dynamical systems and artificial intelligence applied to data banks in geophysics / J. Bonnin (1995)PermalinkRemote sensing in action, RSS95, Proceedings of the 21th annual conference of the Remote Sensing Society RSS, Southampton, 11-14 septembre 1995 / P.J. Curran (1995)PermalinkSystème de cognition artificielle : Application au problème géographique général / Ching-Han Chen (1995)Permalink