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Mapping built-up areas from multitemporal interferometric SAR images: a segment-based approach / Leena Matikainen in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 6 (June 2006)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 6 (June 2006) . - pp 701 - 714 Titre : Mapping built-up areas from multitemporal interferometric SAR images: a segment-based approach Type de document : Article/Communication Auteurs : Leena Matikainen, Auteur ; M.E. Engdahl, Auteur ; Juha Hyyppä, Auteur Année de publication : 2006 Article en page(s) : pp 701 - 714 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] cartographie automatique [Termes IGN] classification dirigée [Termes IGN] densité du bâti [Termes IGN] image ERS-SAR [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] interprétation automatique [Termes IGN] milieu urbain [Termes IGN] segmentation d'image [Termes IGN] utilisation du sol Résumé : (Auteur) Automatic mapping of built-up areas from a multitemporal interferometric ERS-1/2 Tandem dataset was studied. The image data were segmented into homogeneous regions, and the regions were classified as built-up areas, forests, and open areas using their mean intensity and coherence values and additional contextual information. Compared with a set of reference points, an overall classification accuracy of 97 percent was achieved. The classification process was highly automatic and resulted in homogeneous regions resembling a map drawn by a human interpreter. The feasibility of the imagery for dividing built-up areas further into subclasses was also investigated. The results suggest that low-rise areas, high-rise areas, and industrial areas are difficult to distinguish from each other. On the other hand, a correlation between the building density, the proportion of land covered with buildings, and intensity/coherence in the image data was found. The dataset thus appeared to be promising for classifying built-up areas into subclasses according to building density. Copyright ASPRS Numéro de notice : A2006-233 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.72.6.701 En ligne : https://doi.org/10.14358/PERS.72.6.701 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27960 [article]