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Multiple support vector machines for land cover change detection: an application for mapping urban extensions / H. Nemmour in ISPRS Journal of photogrammetry and remote sensing, vol 61 n° 2 (November 2006)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 61 n° 2 (November 2006) . - pp 125 - 133 Titre : Multiple support vector machines for land cover change detection: an application for mapping urban extensions Type de document : Article/Communication Auteurs : H. Nemmour, Auteur ; Y. Chibani, Auteur Année de publication : 2006 Article en page(s) : pp 125 - 133 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Alger [Termes IGN] analyse comparative [Termes IGN] classification par réseau neuronal [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] détection de changement [Termes IGN] occupation du sol [Termes IGN] précision géométrique (imagerie) [Termes IGN] urbanisation Résumé : (Auteur) The reliability of support vector machines for classifying hyperspectral images of remote sensing has been proven in various studies. In this paper, we investigate their applicability for land cover change detection. First, SVM-based change detection is presented and performed for mapping urban growth in the Algerian capital. Different performance indicators, as well as a comparison with artificial neural networks, are used to support our experimental analysis. In a second step, a combination framework is proposed to improve change detection accuracy. Two combination rules, namely, Fuzzy Integral and Attractor Dynamics, are implemented and evaluated with respect to individual SVMs. Recognition rates achieved by individual SVMs, compared to neural networks, confirm their efficiency for land cover change detection. Furthermore, the relevance of SVM combination is highlighted. Copyright ISPRS Numéro de notice : A2006-531 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2006.09.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2006.09.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28254 [article]

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