Extraction of land use / land cover - related information from very high resolution data in urban and suburban areas

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.