Fusing Airborne Laser Scanner Data and Aerial Imagery for the Automatic Extraction of Buildings in Densely Built-up Areas

Using airborne laser scanner data, buildings can be detected automatically, and their roof shapes can be reconstructed. The success rate of building detection and the level of detail of the resulting building models depend on the resolution of the laser scanner data, which is still lower than the resolution of aerial imagery. Building extraction from aerial images alone is difficult because of problems related to shadows, occlusions, and poor contrast. That is why it makes sense to combine these data sources to improve the results of building extraction. This article deals with the fusion of airborne laser scanner data and multi-spectral aerial images for building extraction. There are three instances in the overall process when exploiting the complementary properties of these data appears to be most beneficial: building detection, roof plane detection, and the determination of roof boundaries. Building detection is based on the Dempster-Shafer theory for data fusion. In roof plane detection, the results of a segmentation of the laser scanner data are improved using the digital images. The geometric quality of the roof plane boundaries can be improved at step edges by matching the object edges of the polyhedral models with image edges. Examples are given for a test site in Fairfield (NSW). * Corresponding author.