Efficient management of the territory requires today the availability of comprehensive geographical data, accurate and up to date, supported by powerful databases. In this context, remote sensing data are used for a variety of applications related to urban areas; some examples are land use/cover mapping, urban growth and soil sealing evaluation, detection of green areas, updating of existing maps, energy applications and detection and characterization of buildings. This work aims to highlight how different geomatic techniques and data acquired from heterogeneous surveys can be today used together for producing or updating a digital cartography inside a GIS. The study has been conducted in the urban area of Bologna, Emilia-Romagna region, located in the North of Italy. A high resolution WorldView-2 satellite image and the DSM/DTM, obtained by airborne LiDAR, have been used to obtain a vector layer of the buildings. In particular, to distinguish the buildings among all the elements present in the study area, such as roads, trees, vegetated areas, etc., an object-oriented classification has been performed. This approach, working on groups of pixels (image objects), allows to expand the information content of the basic unit of classification. Therefore, features such as shape, texture and contextual information, coupled with spectral characteristics, potentially allow cartographers to generate products that are competitive, in terms of thematic contents, with those derived from the photo-interpretation. A first application described in this work is to perform a quick change analysis procedure based on the results of the classification compared to an existing numerical cartographic base or a previous classification.