, Expérimentation et évaluation de la méthodologie proposée @prefix DO

, IF { ?O1 a DO:SceneImage. ?O2 a DO:SceneImage. ?O1 DO:hasMin_XBBox ?Min_XBBox1. ?O1 DO:hasMax_XBBox ?Max_XBBox1. ?O1 DO:hasMin_YBBox ?Min_YBBox1. ?O1 DO:hasMax_YBBox ?Max_YBBox1. ?O1 DO:hasMax_YBBox ?Max_YBBox1. ?O1 DO:hasIdentity ?id1. ?O1 DO:hasTime ?t1. ?O2 DO:hasMin_XBBox ?Min_XBBox2. ?O2 DO:hasMax_XBBox ?Max_XBBox2. ?O2 DO:hasMin_YBBox ?Min_YBBox2. ?O2 DO:hasMax_YBBox ?Max_YBBox2. ?O2 DO:hasIdentity ?id2. ?O2 DO:hasTime ?t2. FILTER((?Min_XBBox1 > ?Min_XBBox2) && (?Max_XBBox1 < ?Max_XBBox2) && (Min_YBBox1 > ?Min_YBBox2) && (?Max_YBBox1 < ?Max_YBBox2) && (?t1 < ?t2) && (?id1 = ?id2))

}. Then-{, O1 DO:inside O2

, Règle 5.9 -Règle pour la relation spatio-temporelle inside 143

, Expérimentation et évaluation de la méthodologie proposée @prefix DO

, IF { ?O1 a DO:SceneImage. ?O2 a DO:SceneImage. ?O1 DO:hasMin_XBBox ?Min_XBBox1. ?O1 DO:hasMax_XBBox ?Max_XBBox1. ?O1 DO:hasMin_YBBox ?Min_YBBox1. ?O1 DO:hasMax_YBBox ?Max_YBBox1. ?O1 DO:hasMax_YBBox ?Max_YBBox1. ?O1 DO:hasIdentity ?id1. ?O1 DO:hasTime ?t1. ?O2 DO:hasMin_XBBox ?Min_XBBox2. ?O2 DO:hasMax_XBBox ?Max_XBBox2. ?O2 DO:hasMin_YBBox ?Min_YBBox2. ?O2 DO:hasMax_YBBox ?Max_YBBox2. ?O2 DO:hasIdentity ?id2. ?O2 DO:hasTime ?t2

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, Liste des Publications Chapitre de livre, issue.1

. Ghazouani-f and . R. Farah-i, Semantic Remote Sensing Scenes Interpretation and Change Interpretation, Ontology in Information Science. InTech, 2018. Conférences internationales

. Ghazouani-f and . R. Farah-i, Qualitative semantic spatio-temporal reasoning based on description logics for modeling dynamics of spatio-temporal objects in satellite images, Advanced Technologies for Signal and Image Processing (ATSIP), pp.1-6, 20184.

. Ghazouani-f, W. Messaoudi, and F. I. , Towards an ontological conceptualization for understanding the dynamics of spatio-temporal objects, Advanced Technologies for Signal and Image Processing (ATSIP), pp.543-548, 2016.

. Ghazouani-f, W. Messaoudi, and F. I. , Étude de la dynamique des phénomènes géographiques à travers une modélisation sémantique à base d'ontologie des objets spatiotemporels, ASD 2016 : 10ème Conférence sur les Avancées des Systèmes Décisionnels, 2016.

. Ghazouani-f, W. Messaoudi, and F. I. , A Multi-level Ontological Approach for Change Monitoring in Remotely Sensed Imagery, 7th International Joint Conference on Knowledge Discovery, pp.435-440, 2015.

, Soumis et en révision

. Ghazouani-f and . R. Farah-i, A multi-levels Semantic Scenes Interpretation (SSI) strategy for change interpretation in remote sensing imagery, TGRS : Transactions on Geoscience and Remote Sensing

. Ghazouani-f and . R. Farah-i, Qualitative semantic spatio-temporal reasoning based on description logics for modeling dynamics of spatio-temporal objects in satellite images

, Le terme Description indique les attributs, les caractéristiques et les relations des ressources. Le terme Cadre représente le modèle, les langages et les syntaxes utilisés pour ces descriptions. En RDF, les données sont représen-tées sous la forme d'un graphe-orienté étiqueté. Un graphe RDF est un ensemble de triplets, de la forme <sujet, prédicat, objet>. Le sujet est une ressource qui peut être identifiée par un URI. Le XIV Annexes C. Ontologies prédicat est une spécification réutilisée et identifiée par l'URI de la relation, RDF a été publié comme une recommandation du W3C en 1999 et il a été initialement présenté comme un modèle de données pour les métadonnées

C. La-figure, 3 montre un exemple de triplet RDF décrivant un segment de végétation. Ce segment est vu comme une source (sujet) identifiée par l'URI VPO :VegetationSegment et décrit par le prédicat VPO :hasNDVI et l'

, Comme nous avons introduire, RDF est un langage basé sur XML, ce qui signifie que RDF est capable d'échanger des informations entre d'autres applications basées sur XML. Ces spécifications rendent ce système prêt pour une extensibilité future. Par conséquent, cette performance permet de représenter n'importe quelle ressource et son état, bien que le résultat puisse ne pas être compatible avec le monde réel, ainsi, par exemple, L'utilisation d'un vocabulaire qui possède les URIs pour nommer toutes les ressources de l'ensemble données, est un point fort du langage RDF

, Le langage OWL Le langage OWL (Web Ontology Language) consiste en une suite de recommandations de W3C

. Mcguinness, et il est devenue standard à partir de 4 Février, 2004.

C. Le-langage-de-définitions and W. De-partage-des-ontologies-dans-le, OWL est un langage aussi basé sur XML puisque OWL est une extension de RDF. Par exemple, OWL est très utile pour créer des ontologies universitaires, industrielles, médicales, etc., afin de faciliter l'accès aux données renvoyées vers ces domaines de connaissances. Le langage OWL facilite une plus grande interprétabilité du contenu Web par les machines que celle prise en charge par XML, RDF et RDFS en fournissant un vocabulaire supplémentaire avec une sémantique formelle, 2004.

, triplet RDF) est enrichi avec d'autre concept. L'ensemble de caractéristiques offertes par le langage OWL sont : Une collection d'opérateurs expressifs pour la description de concepts, y compris les opéra-teurs booléens (intersection, union et complément), ainsi que des quantificateurs explicites

, La possibilité de spécifier des caractéristiques de propriétés, telles que la transitivité ou les domaines et les ranges

, Une sémantique bien définie facilitant l'utilisation de l'inférence et du raisonnement automatisé

, L'utilisation des URI pour nommer les concepts et les ontologies

, Un mécanisme pour importer des ontologies externes

, Une compatibilité avec l'architecture du W3C, en particulier d'autres langages de représen-tation tels que RDF et RDFS

C. Figure, OWL full peut être utilisé par quiconque a besoin de sa caractéristique principale : la liberté d'utiliser l'ensemble du spectre du langage OWL, mais, d'autre part, l'exhaustivité informatique n'est pas assurée. OWL DL (Description Logics) impose des restrictions sur la manière dont le vocabulaire peut être utilisé afin de définir un langage pour lequel un certain nombre de tâches de raisonnement clés, 4 -Un exemple d'extension de triplet RDF OWL se base sur RDF et RDFS, mais il ajoute plus de vocabulaire pour décrire les propriétés et les classes et il offre une syntaxe plus forte que RDF et RDFS. En outre

. De-plus, OWL DL peut être utilisé. Il assure le calcul de toutes les conclusions dans une période de temps limitée. OWL Lite restreint davantage l'expressivité autorisée -par exemple

. Baader, Ce langage est généralement utilisé pour des classifications et des contraintes simples grâce à sa simplicité, par exemple, traduire de une taxonomie en thésaurus, où une taxonomie et un thésau-rus sont deux sortes d'ontologies qui sont vraiment étendues, et facilitent ainsi l'utilisation de raisonneurs DL pour fournir un support de raisonnement au langage, 2003.

. Á-partir-de, OWL 2, une version étendue de OWL, est maintenant plus adopté, 2009.

C. , ontologie pour le Web sémantique étendu à partir de OWL 1 et enrichi par XVI Annexes C. Ontologies de nouvelles fonctionnalités

. Motik, OWL 2 EL autorise des axiomes de sous-classe avec intersection, existentielle, mais n'autorise pas la négation, la disjonction, la quantification universelle arbitraire et les inverses de rôle. OWL 2 QL autorise les instructions de sous-propriétés, de domaine, de range et de sous-classe mais il n'autoriser les classes fermées. OWL 2 RL autorise tous les types d'axiomes, les restrictions de cardinalité (seulement ? 1 et ? 0 à droite) et les classes fermées avec un seul membre. Par contre, il interdire certains constructeurs (universels et la négation sur le côté gauche et extensionnels, OWL 2 est supporté par plusieurs raisonneurs sémantiques tels que RacerPro2, Pellet, Hermit et FaCT++. OWL 2 fournit aussi trois profils, 2009.

, SPARQL : un langage d'interrogation des données RÉSOLUTION SPECTRALE

, IR (0,8 -1,1 µm) (B4)

, MIR1, vol.75, issue.1, pp.55-56

, MIR2, vol.35, issue.2, pp.8-10

, MIR1, vol.75, issue.1, pp.55-56

, MIR2, vol.35, issue.2, pp.8-10

, Pan, vol.90, issue.0, pp.52-52

, µm) (B1)

, MIR1, vol.65, issue.1, pp.57-58

, MIR2, vol.29, issue.2, pp.11-13

. Pan1, , vol.68, pp.50-50

, IRT1, vol.19, issue.10, pp.60-71

, IRT2, vol.51, issue.11, pp.50-62

R. Spectrale,

, Pan, vol.73, issue.0, pp.51-51

, IRM, vol.75, issue.1, pp.58-59

, Pan, vol.68, issue.0, pp.61-61

, IRM, vol.75, issue.1, pp.58-59

, Pan, vol.68, issue.0, pp.61-61

, Pan, vol.74, issue.0, pp.45-45

, Pan, vol.74, issue.0, pp.45-45