An Adaptive Strips Method for Extraction Buildings From Light Detection and Ranging Data

A method is proposed for extracting building points set from light detecting and ranging (LiDAR) data. This proposed method is based on a strip strategy to filter building points and extract the edge point set rapidly and effectively in largescale urban building groups. This approach divides the LiDAR data into small strips and classifies each strip of data with an adaptive-weight polynomial in the x- or y-direction. The building edge set can then be extracted by utilizing the regional clustering relationships between points. The results of a series of experiments show that our method can not only filter the LiDAR point cloud, which performs better than existing methods, but also determine the building edge set efficiently, with an average accuracy rate of up to 91.1%.