Generation of 3D city models from airborne laser scanning data

    Dr. -Ing. Norbert Haala

    Institute for Photogrammetry, Stuttgart University
    Keplerstrasse 11, 70174 Stuttgart, Germany
    Tel.: +49-711-121 3383 Fax : +49-711 121 3297
    E-mail: Norbert.Haala@ifp.uni-stuttgart.de
    WWW: www.ifp.uni-stuttgart.de

    For a task like 3D building reconstruction, there are three main data sources carrying information which is required for a highly automated data acquisition. These data sources are aerial images, Digital Surface Models (DSM), which can either be derived by stereo matching from aerial images or be directly measured by scarring laser systems, and -- at least for highly developed countries -- existing (2D) GIS information on the ground plan or usage of buildings. The way these different data sources should be utilized by a process of 3D building reconstruction depends on the distinctive characteristics of the different, partly complementary type of information they contain. Image data contains much information, but just this complexity causes enormous problems for the automatic interpretation of this data type. The GIS as a secondary data source provides information on the 2D shape, i.e., the ground plan of a building, which is very reliable, although information on the third dimension is missing and therefore has to be provided by other data sources. As the information of a DSM is restricted to surface geometry, the interpretation of this kind of data is easier compared to the interpretation of image data. Nevertheless, due to insufficient spatial resolution or quality of the DSM, optimal results can only be achieved by the combination of all data sources. Within this paper two approaches aiming on the combination of aerial images, digital surface models and existing ground plans for the reconstruction of three-dimensional building reconstructions will be demonstrated.

    The main steps of a process for the recognition and reconstruction of objects are object modelling, i.e. the definition and generation of suitable object models, segmentation, i.e. the extraction of primitives from the observed data and matching, I.e. the detection and definition of correspondences between the primitives extracted by the segmentation process and the primitives contained in the object model. A large number of buildings can be represented by a polyhedron since the boundaries of most buildings consist of a number of planar surfaces and straight lines. For this reason a segmentation algorithm should aim to extract planar surfaces and straight lines from the observed data in order to match these features against the corresponding object primitives in the consecutive step of the automatic building reconstruction. Since the use of height data is considered to be the most important topic of this paper, the segmentation of DSM data, which is a prerequisite using this type of data will be discussed in detail. Afterwards two approaches aiming on the combination of different types of information will be presented within this paper. First break-lines extracted from both DSM and image data are used to reconstruct a rather simple type of building. Therefore the high reliability of DSM break-lines are combined with the high geometric accuracy of grey value edges. The second approach aims on the extraction of planar surfaces likely to be roof planes from the DSM. To support this process given ground plans are utilized as a priori information. Within this approach the use of polyhedrons as building models allows to reconstruct very general building types.