Centre de documentation
scientifique

Normalization of TanDEM-X DSM data in urban environments with morphological filters / Christian Geiss in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 8 (August 2015) . - pp 4348 - 4362 Titre : Normalization of TanDEM-X DSM data in urban environments with morphological filters Type de document : Article/Communication Auteurs : Christian Geiss, Auteur ; Michael Wurm, Auteur ; Markus Breunig, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 4348 - 4362 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] Allemagne [Termes IGN] image TanDEM-X [Termes IGN] milieu urbain [Termes IGN] modèle numérique de surface [Termes IGN] modèle numérique de terrain [Termes IGN] montagne [Termes IGN] morphologie mathématique [Termes IGN] Turquie Résumé : (Auteur) The TanDEM-X mission (TDM) is a spaceborne radar interferometer which delivers a global digital surface model (DSM) with an unprecedented spatial resolution. This allows resolving objects above ground such as buildings. Extracting and characterizing those objects in an automated manner represents a challenging problem but opens simultaneously a broad range of large-area applications. In this paper, we discuss and evaluate the suitability of morphological filters (MFs) for the derivation of normalized DSMs from the TDM in complex urban environments and introduce a novel region-growing-based progressive MF procedure. This approach is jointly proposed and can be combined with a postclassification processing scheme to specifically allow for a viable reconstruction of urban morphology in a challenging terrain. The filter approach comprises a multistep procedure using concepts of morphological image filtering, region growing, and interpolation techniques. Therefore, it extends the idea of progressive MFs. The latter aim to identify nonground pixels in the DSM by gradually increasing the size of a structuring element and applying iteratively an elevation difference threshold. After the identification of initial nonground pixels, here, potential nonground pixels are identified within each iteration, and their similarity with respect to neighboring nonground pixels is assessed. Pixels are finally labeled as nonground if a constraint is fulfilled. The postclassification processing scheme adapts techniques of object-based image analyses to further refine regions of classified nonground pixels. Digital terrain models are subsequently generated by interpolating between identified ground pixels. Experimental results are obtained for settlement areas that cover large parts of the cities of Izmir (Turkey) and Wuppertal (Germany). They confirm the capability of the proposed approaches for a reduction of omission errors compared to basic MF-based methods when classifying ground pixe- s, which is favorable in a mountainous terrain with steep slopes. Numéro de notice : A2015-387 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2396195 En ligne : https://doi.org/10.1109/TGRS.2015.2396195 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76866 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2015081	RAB	Revue	Centre de documentation	En réserve L003	Disponible