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A data-mining approach for assessing consistency between multiple representations in spatial databases / David Sheeren in International journal of geographical information science IJGIS, vol 23 n° 7-8 (july 2009)
[article]
Titre : A data-mining approach for assessing consistency between multiple representations in spatial databases Type de document : Article/Communication Auteurs : David Sheeren , Auteur ; Jean Daniel Zucker, Auteur ; Sébastien Mustière , Auteur Année de publication : 2009 Article en page(s) : pp 961 - 992 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] appariement de données localisées
[Termes IGN] apprentissage dirigé
[Termes IGN] base de données localisées
[Termes IGN] cohérence des données
[Termes IGN] découverte de connaissances
[Termes IGN] données vectorielles
[Termes IGN] exploration de données géographiques
[Termes IGN] métadonnées
[Termes IGN] représentation multiple
[Termes IGN] système à base de connaissancesRésumé : (Auteur) When different spatial databases are combined, an important issue is the identification of inconsistencies between data. Quite often, representations of the same geographical entities in databases are different and reflect different points of view. In order to fully take advantage of these differences when object instances are associated, a key issue is to determine whether the differences are normal, i.e. explained by the database specifications, or if they are due to erroneous or outdated data in one database. In this paper, we propose a knowledge-based approach to partially automate the consistency assessment between multiple representations of data. The inconsistency detection is viewed as a knowledge-acquisition problem, the source of knowledge being the data. The consistency assessment is carried out by applying a proposed method called MECO. This method is itself parameterized by some domain knowledge obtained from a second method called MACO. MACO supports two approaches (direct or indirect) to perform the knowledge acquisition using data-mining techniques. In particular, a supervised learning approach is defined to automate the knowledge acquisition so as to drastically reduce the human-domain expert's work. Thanks to this approach, the knowledge-acquisition process is sped up and less expert-dependent. Training examples are obtained automatically upon completion of the spatial data matching. Knowledge extraction from data following this bottom-up approach is particularly useful, since the database specifications are generally complex, difficult to analyse, and manually encoded. Such a data-driven process also sheds some light on the gap between textual specifications and those actually used to produce the data. The methodology is illustrated and experimentally validated by comparing geometrical representations and attribute values of different vector spatial databases. The advantages and limits of such partially automatic approaches are discussed, and some future works are suggested. Copyright Taylor & Francis Numéro de notice : A2009-342 Affiliation des auteurs : IGN+Ext (1940-2011) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/13658810701791949 En ligne : http://doi.org/10.1080/13658810701791949 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29972
in International journal of geographical information science IJGIS > vol 23 n° 7-8 (july 2009) . - pp 961 - 992[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-09051 RAB Revue Centre de documentation En réserve L003 Disponible 079-09052 RAB Revue Centre de documentation En réserve L003 Disponible Developing collaborative classifiers using an Expert-based Model / Giorgos Mountrakis in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 7 (July 2009)
[article]
Titre : Developing collaborative classifiers using an Expert-based Model Type de document : Article/Communication Auteurs : Giorgos Mountrakis, Auteur ; R. Watts, Auteur ; L. Luo, Auteur ; Jing Wang, Auteur Année de publication : 2009 Article en page(s) : pp 831 - 843 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classificateur
[Termes IGN] classification à base de connaissances
[Termes IGN] image Landsat
[Termes IGN] Las Vegas
[Termes IGN] mise à l'échelle
[Termes IGN] précision de la classification
[Termes IGN] surface imperméable
[Termes IGN] système expertRésumé : (Auteur) This paper presents a hierarchical, multi-stage adaptive strategy for image classification. We iteratively apply various classification methods (e.g., decision trees, neural networks), identify regions of parametric and geographic space where accuracy is low, and in these regions, test and apply alternate methods repeating the process until the entire image is classified. Currently, classifiers are evaluated through human input using an expert-based system; therefore, this paper acts as the proof of concept for collaborative classifiers. Because we decompose the problem into smaller, more manageable sub-tasks, our classification exhibits increased flexibility compared to existing methods since classification methods are tailored to the idiosyncrasies of specific regions. A major benefit of our approach is its scalability and collaborative support since selected low-accuracy classifiers can be easily replaced with others without affecting classification accuracy in high accuracy areas. At each stage, we develop spatially explicit accuracy metrics that provide straightforward assessment of results by non-experts and point to areas that need algorithmic improvement or ancillary data. Our approach is demonstrated in the task of detecting impervious surface areas, an important indicator for human-induced alterations to the environment, using a 2001 Landsat scene from Las Vegas, Nevada. Copyright ASPRS Numéro de notice : A2009-263 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.7.831 En ligne : https://doi.org/10.14358/PERS.75.7.831 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29893
in Photogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 7 (July 2009) . - pp 831 - 843[article]A GeoAgent-based framework for knowledge-oriented representation: embracing social rules in GIS / C. Yu in International journal of geographical information science IJGIS, vol 23 n° 7-8 (july 2009)
[article]
Titre : A GeoAgent-based framework for knowledge-oriented representation: embracing social rules in GIS Type de document : Article/Communication Auteurs : C. Yu, Auteur ; Donna J. Peuquet, Auteur Année de publication : 2009 Article en page(s) : pp 923 - 960 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] agent (intelligence artificielle)
[Termes IGN] base de connaissances
[Termes IGN] base de règles
[Termes IGN] cadre conceptuel
[Termes IGN] interaction homme-milieu
[Termes IGN] modèle conceptuel de données localisées
[Termes IGN] Pennsylvanie (Etats-Unis)
[Termes IGN] prototype
[Termes IGN] représentation des connaissances
[Termes IGN] système à base de connaissances
[Termes IGN] système multi-agentsRésumé : (Auteur) While current Geographic Information Systems (GISs) can represent observational spatial data well, they have limited capabilities in representing some non-observational social elements and goal-driven behaviours that can be important factors in a wide range of geographic issues. Such social components may include laws, regulations, polices, plans, culture, and customs, as well as their relations and interactions with the geographic environment at different scales. Getting beyond traditional data-centred approaches, this research presents a knowledge-oriented strategy in order to address these issues within a GIS context. We incorporate two major conceptual elements. First, extending from conventional agent notions and their geographic applications, geographic agents (GeoAgents) are considered as a basic representation component to specifically address social rules and goal-driven behaviours that impact the Earth and environmental systems. Second, in order to incorporate GeoAgents with current space-time representation, a new conceptual representation framework, called 'fields, objects, time, GeoAgents, and relations' (FOTAR), is introduced to address the cross-scale processes of both social and natural interactions. A Java-based prototype, GeoAgent-based Knowledge System (GeoAgentKS), is described to implement this framework by integrating agent technologies with multiple data and knowledge representation techniques, such as expert systems, concept maps, mathematical models, and geospatial databases. The application of this prototype in a case study is also presented, investigating scale-dependent human-environment interactions under different emergency situations for community water systems in Central Pennsylvania, USA. In this case study, a systematic set of methodologies of knowledge acquisition, representation, and confirmation for constructing GeoAgents' knowledge bases by using expert systems were explored to formalize high-level knowledge and social behaviours in the FOTAR-based representations. The results show that the proposed conceptual representation framework is achievable at both implementation and application levels, and the prototype tool is demonstrated to be valuable in facilitating knowledge sharing, policymaking, municipal management, and decision-making, especially for real-world emergency management. Copyright Taylor & Francis Numéro de notice : A2009-341 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/13658810701602104 En ligne : https://doi.org/10.1080/13658810701602104 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29971
in International journal of geographical information science IJGIS > vol 23 n° 7-8 (july 2009) . - pp 923 - 960[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-09051 RAB Revue Centre de documentation En réserve L003 Disponible 079-09052 RAB Revue Centre de documentation En réserve L003 Disponible Tropical cyclone trend analysis using enhanced parallel coordinates and statistical analytics / C.A. Steed in Cartography and Geographic Information Science, vol 36 n° 3 (July 2009)
[article]
Titre : Tropical cyclone trend analysis using enhanced parallel coordinates and statistical analytics Type de document : Article/Communication Auteurs : C.A. Steed, Auteur ; P. Fitzpatrick, Auteur ; et al., Auteur Année de publication : 2009 Article en page(s) : pp 251 - 265 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de données
[Termes IGN] corrélation
[Termes IGN] cyclone
[Termes IGN] découverte de connaissances
[Termes IGN] données environnementales
[Termes IGN] données météorologiques
[Termes IGN] données statistiques
[Termes IGN] régressionRésumé : (Auteur) This work presents, via an in-depth case study on how parallel coordinates coupled with statistical analysis can be used for more effective knowledge discovery and confirmation in complex, environmental data sets. Advanced visual interaction techniques such as dynamic axis scaling, conjunctive parallel coordinates, statistical indicators, and aerial perspective shading are combined into an interactive geovisual analytics system. Moreover, the system facilitates statistical processes such as stepwise regression and correlation analysis to assist in the identification and quantification of the most significant predictors for a particular dependent variable. Using a systematic workflow, this approach is demonstrated via a North Atlantic hurricane climate study in close collaboration with a domain expert. By revealing several important physical associations, the case study confirms that the visual analytics approach facilitates a deeper understanding of multidimensional climate data sets when compared to traditional techniques. Copyright CaGISociety Numéro de notice : A2009-269 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1559/152304009788988314 En ligne : https://doi.org/10.1559/152304009788988314 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29899
in Cartography and Geographic Information Science > vol 36 n° 3 (July 2009) . - pp 251 - 265[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-09031 RAB Revue Centre de documentation En réserve L003 Disponible Techniques cartographiques : l'automatisation de la cartographie / Anne Ruas in Le monde des cartes, n° 200 (juin 2009)
[article]
Titre : Techniques cartographiques : l'automatisation de la cartographie Type de document : Article/Communication Auteurs : Anne Ruas , Auteur Année de publication : 2009 Article en page(s) : pp 115 - 121 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Cartographie numérique
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] système expertRésumé : (documentaliste) A l'occasion du 200ème numéro du Bulletin du Comité Français de Cartographie devenu Monde des Cartes, les membres actuels reprennent des articles marquants pour chacun un intérêt dans le pan de la cartographie dont ils ont repris le flambeau. Madame Ruas a retenu des articles de J.P. Grelot et C. Müller, décrivant les avancées de l'informatique dans la structuration et le traitement de données dont la généralisation profite. Numéro de notice : A2009-236 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29866
in Le monde des cartes > n° 200 (juin 2009) . - pp 115 - 121[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 021-09021 RAB Revue Centre de documentation En réserve L003 Disponible 021-09022 RAB Revue Centre de documentation En réserve L003 Disponible Multi-scale rendering with geometry collapse and a symbol knowledge Base / J. Choi in Cartographic journal (the), vol 46 n° 2 (May 2009)PermalinkTeraGrid GIScience Gateway: Bridging cyberinfrastructure and GIScience / Shaowen Wang in International journal of geographical information science IJGIS, vol 23 n° 5 (may 2009)PermalinkAnalyse exploratoire des effets de support spatial et de robustesse statistique sur la fiabilité de la mesure de la (bio)diversité / Didier Josselin in Photo interprétation, European journal of applied remote sensing, vol 45 n° 1 (mars 2009)PermalinkApplication of Terrestrial Laser Scanning for knowledge extraction from archaeological excavation / J. Marchand in Geomatica, vol 63 n° 1 (March 2009)PermalinkApport des règles d'association spatiales pour l'alimentation automatique des bases de données géographiques / S.Y. Turki in Revue internationale de géomatique, vol 19 n° 1 (mars – mai 2009)Permalinkvol 45 n° 1 - mars 2009 - Géomatique et environnement urbain, [actes], Rennes, 28 juin 2007 (Bulletin de Photo interprétation, European journal of applied remote sensing)PermalinkMining long, sharable patterns in trajectories of moving objects / G. Gidofalvi in Geoinformatica, vol 13 n° 1 (March 2009)PermalinkMise en oeuvre d'une mémoire environnementale adaptée aux besoins d'un observatoire du domaine côtier : MEnIr / Cyril Faucher in Revue internationale de géomatique, vol 19 n° 1 (mars – mai 2009)PermalinkTopological feature vectors for exploring topological relationships / R. Praing in International journal of geographical information science IJGIS, vol 23 n°3-4 (march - april 2009)PermalinkCOSIT 2009, Doctoral Colloquium, 25 septembre 2009, Port de l'Aber Wrac'h, France / Clare Davies (2009)Permalink