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Knowledge-based approaches to accurate mapping of mangroves from satellite data / J. Gao in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 11 (November 2004)
[article]
Titre : Knowledge-based approaches to accurate mapping of mangroves from satellite data Type de document : Article/Communication Auteurs : J. Gao, Auteur ; H. Chen, Auteur ; Y. Zhang, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 1241 - 1248 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] Auckland
[Termes IGN] carte de la végétation
[Termes IGN] carte thématique
[Termes IGN] classificateur paramétrique
[Termes IGN] classification à base de connaissances
[Termes IGN] classification dirigée
[Termes IGN] image SPOT
[Termes IGN] littoral
[Termes IGN] mangrove
[Termes IGN] précision sémantique
[Termes IGN] raisonnement spatialRésumé : (Auteur) Mangroves are difficult to map accurately from satellite data by means of parametric classification because of their spectral similarity to other coastal vegetation despite their habitat being inside coastal waters. This study aims to improve the mapping accuracy through incorporation of such spatial knowledge about mangroves in the Waitemata Harbor of Auckland, New Zealand, from SPOT data. The spatial knowledge was combined with spectral knowledge in the mapping. Supervised classification was found to map stunted and lush mangroves at an accuracy of, respectively, 46.7 percent and 68.3 percent. These accuracy levels rose, respectively, to 83.3 percent and 96.7 percent after the spatial knowledge was sequentially incorporated into the mapping. A similar accuracy level was achieved from knowledge-based spatial reasoning. If integrated simultaneously with spectral knowledge, spatial knowledge did not improve the accuracy noticeably because of difficulty in gaining quality spectral knowledge. It is concluded that knowledge-based, post-classification processing considerably improves the accuracy of mapping mangroves over parametric classification. Numéro de notice : A2004-456 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.70.11.1241 En ligne : https://doi.org/10.14358/PERS.70.11.1241 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26976
in Photogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 11 (November 2004) . - pp 1241 - 1248[article]Using Thematic Mapper data for change detection and sustainable use of cultivated land: a case study in the Yellow River delta, China / G.X. Zhao in International Journal of Remote Sensing IJRS, vol 25 n° 13 (July 2004)
[article]
Titre : Using Thematic Mapper data for change detection and sustainable use of cultivated land: a case study in the Yellow River delta, China Type de document : Article/Communication Auteurs : G.X. Zhao, Auteur ; G. Lin, Auteur Année de publication : 2004 Article en page(s) : pp 2509 - 2522 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] agriculture
[Termes IGN] analyse diachronique
[Termes IGN] Chine
[Termes IGN] classification à base de connaissances
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] delta
[Termes IGN] détection de changement
[Termes IGN] développement durable
[Termes IGN] Fleuve jaune (Chine)
[Termes IGN] image Landsat-TM
[Termes IGN] surface cultivée
[Termes IGN] utilisation du solRésumé : (Auteur) Preservation of cultivated land is one of China's four basic strategic policies. Timely land use monitoring is a prerequisite of cultivated land management and sustainable utilization. Using digital satellite remote sensing techniques, the intention is to develop a workable procedure for cultivated land change detection in the Yellow River delta region. Four detection methods were assessed. The assessment, in general, suggests that it is difficult to find a single efficient method for cultivated land change detection in the study area, where spectral confusion is widespread due to soil salinization and juxtaposed land use patterns. The knowledge-based visual change detection and classification-result overlay methods are more appropriate than the multi-temporal composite and classification, and image ratioing. The latter two methods are useful and efficient when remote sensing data acquired in the suitable season are available, and distinct spectral characteristics of different land use types exist. The results show that the area of cultivated land in this region decreased by 5321.8 ha over the period 1987 to 1998, i.e. 483.8ha every year, mainly concentrated in the central paddy field region and northeast dry land region. Numéro de notice : A2004-258 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160310001619571 En ligne : https://doi.org/10.1080/01431160310001619571 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26785
in International Journal of Remote Sensing IJRS > vol 25 n° 13 (July 2004) . - pp 2509 - 2522[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04111 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Towards an operational system for automated updating of road databases by integration of imagery and geodata / C. Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 58 n° 3-4 (January - June 2004)
[article]
Titre : Towards an operational system for automated updating of road databases by integration of imagery and geodata Type de document : Article/Communication Auteurs : C. Zhang, Auteur Année de publication : 2004 Article en page(s) : pp 166 - 186 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données routières
[Termes IGN] classification à base de connaissances
[Termes IGN] données vectorielles
[Termes IGN] extraction du réseau routier
[Termes IGN] extraction semi-automatique
[Termes IGN] mise à jour cartographique
[Termes IGN] mise à jour de base de données
[Termes IGN] objet géographique 3D
[Termes IGN] objet géographique linéaire
[Termes IGN] reconstruction 3D
[Termes IGN] réseau routier
[Termes IGN] test de performanceRésumé : (Auteur) The extraction of road networks from aerial images is one of the current challenges in digital photogrammetry and computer vision. In this paper, we present a practical system for 3D road network reconstruction from aerial images using knowledgebased image analysis. In contrast to other approaches, the developed system integrates processing of color image data and information from digital spatial databases, extracts and fuses multiple object cues, takes into account context information, employs existing knowledge, rules and models, and treats each road subclass accordingly. The key of the system is the use of knowledge as much as possible to increase success rate and reliability of the results, working in 2D images and 3D object space, and use of 2D and 3D interaction when needed. Another advantage of the developed system is that it can correctly and reliably handle problematic areas caused by shadows and occlusions. This work is part of a project to improve and update the 1:25,000 vector maps of Switzerland. The system has been implemented as a stand-alone software package, and has been tested on a large number of images with different landscape. In this paper, various parts of the developed system are discussed, and the results of our system in recent benchmark tests conducted independently by our project partner in Switzerland, and the test results with black and white images in a test site in Belgium are presented together with the system performance evaluation. Copyright ISPRS Numéro de notice : A2004-049 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2003.09.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2003.09.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26577
in ISPRS Journal of photogrammetry and remote sensing > vol 58 n° 3-4 (January - June 2004) . - pp 166 - 186[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-04012 RAB Revue Centre de documentation En réserve L003 Disponible 081-04011 RAB Revue Centre de documentation En réserve L003 Disponible Integration of classification methods for improvement of land-cover map accuracy / XiaoHang Liu in ISPRS Journal of photogrammetry and remote sensing, vol 56 n° 4 (July - August 2002)
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Titre : Integration of classification methods for improvement of land-cover map accuracy Type de document : Article/Communication Auteurs : XiaoHang Liu, Auteur ; Andrew K. Skidmore, Auteur ; H.V. Oosten, Auteur Année de publication : 2002 Article en page(s) : pp 257 - 268 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification à base de connaissances
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par réseau neuronal
[Termes IGN] occupation du solRésumé : (Auteur) Classifiers, which are used to recognize patterns in remotely sensing images, have complementary capabilities. This study tested whether integrating the results from individual classifiers improves classification accuracy. Two integrated approaches were undertaken. One approach used a consensus builder (CS13) to adjust classification output in the case of disagreement in classification between maximum likelihood classifier (MLC), expert system classifier (ESC) and neural network classifier (NNC). If the output classes for each individual pixel differed, the producer accuracies for each class were compared and the class with the highest producer accuracy was assigned to the pixel. The consensus builder approach resulted in a classification with a slightly lower accuracy (72%) when compared with the neural network classifier (74%), but it did significantly better than the maximum likelihood (62%) and expert system (59%) classifiers. The second approach integrated a rulebased expert system classifier and a neural network classifier. The output of the expert system classifier was used as one additional new input layer of the neural network classifier. A postprocessing using the producer accuracies and some additional expert rules was applied to improve the output of the integrated classifier. This is a relatively new approach in the field of image processing. This second approach produced the highest overall accuracy (80%). Thus, incorporating correct, complete and relevant expert knowledge in a neural network classifier leads to higher classification accuracy. Copyright ISPRS Numéro de notice : A2002-168 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/S0924-2716(02)00061-8 En ligne : https://doi.org/10.1016/S0924-2716(02)00061-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22083
in ISPRS Journal of photogrammetry and remote sensing > vol 56 n° 4 (July - August 2002) . - pp 257 - 268[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-02021 SL Revue Centre de documentation Revues en salle Disponible Wissensbasierte Interpretation von Vegetationsflächen aus multitemporalen Fernerkundungsdaten / Kian Pakzad (2001)
Titre : Wissensbasierte Interpretation von Vegetationsflächen aus multitemporalen Fernerkundungsdaten Titre original : [L'interprétation basée sur les connaissances des surfaces végétales a partir de données de télédétection multi temporelles] Type de document : Thèse/HDR Auteurs : Kian Pakzad, Auteur Editeur : Munich : Bayerische Akademie der Wissenschaften Année de publication : 2001 Collection : DGK - C Sous-collection : Dissertationen num. 543 Importance : 104 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-3-7696-9582-3 Note générale : Bibliographie Langues : Allemand (ger) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] classification à base de connaissances
[Termes IGN] image multitemporelle
[Termes IGN] interprétation automatique
[Termes IGN] lande
[Termes IGN] réseau sémantique
[Termes IGN] segmentation d'image
[Termes IGN] surveillance de la végétation
[Termes IGN] système expertRésumé : (Auteur) The thesis in hand presents a general concept for the automatic interpretation of remote sensing data with the interpretation of vegetation areas brought into focus, which uses both structural features and temporal knowledge. Based on this concept, a method for automatic multitemporal interpretation of moorland is explained. The developed procedures rely on a knowledge based image analysis system, which uses Semantic Nets for knowledge representation in standard language. During the interpretation process these are used for deriving hypotheses by applying a continuous symbolic processing, to verify them, and thus gain a symbolic description of the examined landscape scene. Verification of the hypotheses is carried out in the remote sensing data using specific processing operators.
The introduced general concept for interpretation of remote sensing data groups the object classes found in the landscape into various categories, according to their characteristics. Thus object classes were discerned which possess a given geometry, given texture, given pattern, or characteristic features. Interpretation strategies are suggested for each category, which relate to the creation of the semantic nets as well as to the specific image processing operators. Then the interpretation of vegetation areas belonging to the latter category is brought into focus. As such areas often are inhomogeneous and show numerous structures, the approaches of multispectral classification applied so far are less suitable as they result in oversegmentation, and either do not or to a little extent utilize structural features for interpretation. The new strategy presented here proceeds from given segment borders and searches for structural features within the borders. Such structural features are described by standard language and may be for example "tracks", "irregular structure", or "vegetation". Their verification in the images is done by feature analysis operators.
For interpretation of temporal changes a new concept is suggested, which discretely describes temporal conditions of regions, and which transfers the most probable temporal changes of the given conditions as temporal knowledge into a state transition diagram, then using it for multitemporal interpretation. Thus the temporal history of the past interpretations is used for the interpretation of images of a particular epoch by favouring certain interpretation methods, and a priori excluding others.
Based on the described approaches a procedure for automatic multitemporal interpretation of industrially used moorland was successfully developed. Proceeding from an initial segmentation based on GeoData a resegmentation and an interpretation of the segments is carried out for each investigated epoch. By using temporal knowledge it is possible to separate moor classes, which can only be detected in temporal order. The application of temporal knowledge and structural features enables the exclusive use of grey scale images for interpretation of vegetation areas. The results show that the presented procedure is suitable for multitemporal interpretation of moorland, and that it is able to distinguish additional moor classes compared to the approaches used so far. It is further applicable for a more robust multitemporal interpretation, and does not depend on colour images.Numéro de notice : 13067 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=54867 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 13067-01 35.41 Livre Centre de documentation Télédétection Disponible L'extraction des voies de communication sur les images satellitaires SPOT : Nexsys, un système semi-automatique d'aide pour la cartographie basé sur la connaissance / J.M. Gilliot in Bulletin du comité français de cartographie, n° 142 - 143 (mars - août 1995)PermalinkKnowledge-based classification of an urban area using texture and context information in Landsat-TM imagery / L. Moller-Jensen in Photogrammetric Engineering & Remote Sensing, PERS, vol 56 n° 6 (june 1990)PermalinkKnowledge-based techniques for multi-source classification / A. Srinivasan in International Journal of Remote Sensing IJRS, vol 11 n° 3 (March 1990)PermalinkKnowledge-based GIS techniques applied to geological engineering / E. Lynn Usery in Photogrammetric Engineering & Remote Sensing, PERS, vol 54 n° 11 (november 1988)Permalink