A greyscale voxel model for airborne lidar data applied to building detection

Abstract

The existing binary voxel model algorithm for 3D building detection (3BD) from airborne lidar cannot distinguish between connected buildings and non‐buildings. As a result, a greyscale voxel structure model, using the discretised mean intensity of lidar points, is presented to support subsequent building detection in areas where buildings are adjacent to non‐buildings but with different greyscales. The resulting 3BD algorithm first detects a building roof by selecting voxels characterised by a jump in elevation as seeds, labelling them and their 3D connected regions as rooftop voxels. Then voxels which fall into buffers and possess similar greyscales to that of the corresponding building outline are assigned as building façades. The results for detected buildings are evaluated using lidar data with different densities and demonstrate a high rate of success.

An improved RANSAC algorithm for extracting roof planes from airborne lidar data

“…Area 2: Vaihingen, Germany . Another study area was chosen from the Vaihingen dataset of ISPRS (), which has been used in many photogrammetric building studies (for example, Wang et al., ). In the selected study area, there are six large building roof planes.…”

“…Building roof plane extraction has been studied in various research studies over the past decade (Satari et al., ; Awrangjeb and Fraser, ; Potúčková and Hofman, ; Tomljenovic et al., ; Cao et al., ; Wang et al., ; Zhang et al., ). Different algorithms are presented to extract planar features.…”

“…and accurate 3D point data (Flood, 2001;Lefsky et al, 2002) by calculating a laser beam's travel time. Using lidar data, features of interest can be extracted from the whole dataset.Building roof plane extraction has been studied in various research studies over the past decade (Satari et al, 2012;Awrangjeb and Fraser, 2014; Pot u ckov a and Hofman, 2016;Tomljenovic et al, 2016;Cao et al, 2017;Wang et al, 2018;Zhang et al, 2018). Different algorithms are presented to extract planar features.…”