Morphology-based Building Detection from Airborne Lidar Data

The advent of Light Detection and Ranging (lidar) technique Provides a promising resource for three-dimensional building detection. Due to the difficulty of removing vegetation, most building detection methods fuse lidar data with multi-spectral images for vegetation indices and relatively few approaches use only lidar data. However, the fusing process may cause errors, introduced by resolution and time difference, shadow and high-rise building displacement problems, and the geo-referencing process. This research presents a morphological building detecting method to identify buildings by gradually removing non-building pixels. First, a ground-filtering algorithm separates ground pixels with buildings, trees, and other objects. Then, an analytical approach removes the remaining non-building pixels using size, shape, height, building element structure, and the height difference between the first and last returns. The experimental results show that this method provides a comparative performance with an overall accuracy of 95.46 percent as in a study site in Austin urban area.