Basemaps are the main resource used in urban planning, building and infrastructure asset management. Therefore, they must be accurate and up to date to better serve citizens, contractors, property owners and town planning departments. Traditionally, they have been updated by aerial photogrammetry, but this is not always possible and alternatives need to be sought. In such cases, a useful option for large scales is the mobile mapping system (MMS). However, automatic extraction from MMS point clouds is limited by the complexity of the urban environment. Therefore, the influence of the urban pattern is analysed in three zones with varied urban characteristics: areas with high buildings, open areas, and areas with a low level of urbanization. In these areas, the capture and automatic extraction of 3D urban elements is performed using commercial software, which is useful for some elements but not for manholes. The objective of this study is to establish a methodology for extracting manholes automatically and completing hidden buildings' corners, in order to update urban basemaps. Shape and intensity are the main detection parameters for manholes, whereas additional information from satellite image Quickbird is used to complete the buildings. The worst rate of detection for all the extracted urban elements was found in areas of high buildings. Finally, the article analyses the computing cost for manhole extraction, and the economic cost and time consume of the entire process, including the proposed methodology using an MMS point cloud and the traditional survey in this case.