Automatic Building Extraction from Airborne Laser Scanning Data

Laser scanning is a new technology for obtaining Digital Surface Models (DSM) of the earth surface. It is fast method for sampling the earth surface with a high density and high point accuracy. In this paper a procedure for building detection and roof extraction from the DSM is presented. The procedure starts by re-sampling elevation as obtained by laser scanning into regular grid. The core part of the building detection is based on a morphological filter for distinguishing between terrain and non-terrain segments. The non-terrain segments are classified into building or vegetation. Aiming at a vector representation of buildings the roof faces are obtained by further segmentation of the building segments into sub-segments. The 3D geometrical properties of each face are obtained based on plane fitting using least squares adjustment. The reconstruction part of the procedure is based on the adjacency among the roof faces. Primitive extraction and face intersections are used for roof reconstruction. Prior knowledge about the buildings and terrain is needed for both the detection and extraction processes. The procedure is developed to work for all terrain types and for many building/roof types. The laser data used in this research have an average density of 2-3 points per square meter and 0.10m standard deviation of the elevation values. The procedure shows promising results for building detection. The reconstruction part shows promising results for some roof faces, obtaining high planimetric and height accuracy. Some adaptations of the procedure are recommended for enhancing the performance of the presented approach.