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                <term xml:lang="fr">Télédétection hyperspectrale</term>
                <term xml:lang="fr">Environnement urbain</term>
                <term xml:lang="fr">Bases de données spectrales</term>
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              <p>L'imagerie hyperspectrale (IH) est à l’heure actuelle encore trop peu considérée, pourtant ses spécificités en font un auxiliaire de poids pour le suivi des éléments du milieu urbain. Le projet HYEP a pour objectif de proposer un panel de méthodes et de traitements appliqués à l’imagerie hyperspectrale tout en comparant à celles d’autres capteurs existants. Si l’IH est complémentaire aux capteurs actuels car plus riche spectralement, elle permet d'identifier et de caractériser autrement les éléments naturels ou anthropiques. Pour ce faire les méthodes d'extraction d'information doivent être adaptées, voire créées. Le volet méthodologique du projet est ancré à la fois dans la solidification des approches actuelles et le test de méthodes ou adaptées ou nouvelles. Nos résultats ont été présentés tout au long du projet à la communauté scientifique et aux collectivités territoriales. Un des intérêts des travaux a été la comparaison des résultats à différentes résolutions spatiales pour préciser le gain d’un tel capteur hyperspectral par rapport à ceux existants ou à venir. Données et Méthodes : Utilisation et adaptation de méthodes courantes en télédétection 1200. Les méthodes déployées ont été choisies parmi l’ensemble des méthodes existantes en les adaptant au type de signal, au nombre de bandes spectrales et aux caractéristiques du milieu. Ainsi les données étant issues de survol aérien les premiers développements ont été réalisés pour s’affranchir des effets de l’atmosphère (correction atmosphérique des images hyperspectrales– 3 méthodes testées) et une base de données de signatures morphospectrales pour divers éléments d'occupation du sol en ville (toits, routes, la végétation etc.) permettant de mieux cerner les valeurs spectrales des matériaux a été établie. Elle comprend des données de littérature, des mesures in situ et en laboratoire. Ses apports dans différents traitements declassification ont été testés. Des méthodes d’extraction, de fusion ou de classification ont été utilisées à différentes résolutions spatiales et spectrales afin de spécifier les gains par rapport à d’autres capteurs. Des méthodes de classifications et de démélange ont été adaptées. Des indices de forme facilitant la classification d’image en milieux urbain ont été testés et/ou développés. Résultats majeurs et faits marquant - 3 méthodes de correction atmosphériques développées et comparées en fonction de la résolution spatiale ; - Adaptation de méthodes de fusion (pan ou multi sharpening) et de démélange. - Transfert : Mise en place à Kaunas (Lituanie) du développement complet de l’approche. - Algorithmes</p>
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