Reference : Extraction of land use / landcover – related information from very high resolution da...
Scientific congresses and symposiums : Paper published in a book
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
http://hdl.handle.net/2268/5050
Extraction of land use / landcover – related information from very high resolution data in urban and suburban areas
English
Van de Voorde, Tim mailto [Vrije Universiteit Brussel - VUB > geografie > Cartography and GIS Research Unit (CGIS) > >]
De Genst, William [Vrije Universiteit Brussel - VUB > geografie > Cartography and GIS Research Unit (CGIS) > >]
Canters, Frank mailto [Vrije Universiteit Brussel - VUB > geografie > Cartography and GIS Research Unit (CGIS) > >]
Stephenne, Nathalie [Université Libre de Bruxelles - ULB > géographie > Institut de Gestion de l’Environnement et d’Aménagement du Territoire (IGEAT) > >]
Wolff, Éléonore mailto [Université Libre de Bruxelles - ULB > géographie > Institut de Gestion de l’Environnement et d’Aménagement du Territoire (IGEAT) > >]
Binard, Marc mailto [Université de Liège - ULg > Département de géographie > Labo Surfaces - Unité de Géomatique - Geomatics Unit > >]
2004
Remote Sensing in Transition
Goossens, Rudi mailto
Millpress
237-244
No
International
90 5966 007 2
Rotterdam
Netherlands
23rd symposium of the EARSeL
du 2 au 5 juin 2003
EARSeL
Gent
Belgium
[en] VHR satellite images ; urban remote sensing, ; land-cover classification
[en] Very High Resolution (VHR) satellite images offer a great potential for the extraction of landuse and land-cover related information for urban areas. The available techniques are diverse and need to be further examined before operational use is possible. In this paper we applied two pixel-by-pixel classification techniques and the object-oriented image analysis approach (eCognition) for a land-cover classification of a Quickbird image of a study area in the northern part of the city of Ghent (Belgium). Only small differences in overall Kappa were noted between the best results of the pixel-based approach (neural network classification with Haralick texture measures) and the object-oriented classification (eCognition). A rule-based procedure using ancillary information on elevation derived from a digital surface model was applied on the pixel-based land-cover classification in order to obtain information on the spatial distribution of buildings and artificial surfaces.
Laboratoire SURFACES
Politique Scientifique Fédérale (Belgique) = Belgian Federal Science Policy
SPIDER
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/5050
http://www.vub.ac.be/spider/intro.html

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