A New Approach to Urban Modelling Based on LIDAR

Abstract

Estimating building forms from LIDAR data has usually been done by attempting to fit standardized building types to the residual data points after an estimated bare earth terrain surface has been removed. We propose an approach based on segmenting the raw data into high and low regions, and then modelling the walls and roofs by extruding the triangulated terrain surface (TIN) using CAD-type Euler operators. The segmentation may be done by the addition of building boundary data to the TIN so as to force triangle edges to match the boundaries, and then using Euler operators to extrude the building, producing vertical walls rather than the more usual sloping walls formed from TIN models alone. If boundary data is not available then an automated segmentation method based on adaptive Voronoi cells may be used, so that each cell contains either high or low LIDAR data, but not both. This prismatic model, with flat-topped cells, approximates the building forms without hypothesizing specific building types. Once the segmentation is achieved, and the walls constructed, we attempt to model the roofs by calculating the eigenvalues and eigenvectors of the vector normals of the TIN sections within the building boundaries. The smallest eigenvalue gives a predicted roof orientation, and the resulting roof profile is then modelled.