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Detection of buildings at airport sites using images and lidar data and a combination of various methods / N. Demir (2009)  

Public contenu dans CMRT09 Object extraction for 3D city models, road databases and traffic monitoring-concepts, algorithms and evaluation / Uwe Stilla (2009)   Titre : Detection of buildings at airport sites using images and lidar data and a combination of various methods Type de document : Article/Communication Auteurs : N. Demir, Auteur ; Daniela Poli, Auteur ; Emmanuel P. Baltsavias, Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2009 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 38-3-W4 Conférence : CMRT 2009, City Models, Roads and Traffic, Object extraction for 3D city models, road databases, traffic monitoring 03/09/2009 04/09/2009 Paris France OA ISPRS Archives Importance : pp 71 - 76 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] aéroport [Termes IGN] classification dirigée [Termes IGN] données lidar [Termes IGN] image aérienne [Termes IGN] modèle numérique de terrain [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] Zurich (Suisse) Résumé : (Auteur) In this work, we focus on the detection of buildings, by combining information from aerial images and Lidar data. We applied four different methods on a dataset located at Zurich Airport, Switzerland. The first method is based on DSM/DTM comparison in combination with NDVI analysis (Method 1). The second one is a supervised multispectral classification refined with a normalized DSM (Method 2). The third approach uses voids in Lidar DTM and NDVI classification (Method 3), while the last method is based on the analysis of the density of the raw Lidar DTM and DSM data (Method 4). An improvement has been achieved by fusing the results of the different methods, taking into account their advantages and disadvantages. Edge information from images has also been used for quality improvement of the detected buildings. The accuracy of the building detection was evaluated by comparing the results with reference data, resulting in 94% detection and 7% omission errors for the building area. Numéro de notice : C2009-009 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Communication DOI : sans En ligne : https://www.isprs.org/proceedings/XXXVIII/3-W4/pub/CMRT09_71.pdf Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=65049