Modeling of buildings in dense urban areas from airborne LiDAR and aerial photograph

Abstract

In this paper, an algorithm is proposed for automatically generating three-dimensional (3D) building models in dense urban areas. The proposed algorithm uses the results of building segmentation from aerial photographs. After airborne light detection and ranging (LiDAR) data are filtered, point clouds are classified into small groups, and the principal azimuthal directions are determined. Normals to the roofs of the buildings are then determined in order to keep consistency with the direction of the group of roofs. By considering the segmented regions and the normals, models of actual building types-gable-roof, hip-roof, flat-roof and slant-roof buildings-are generated. The proposed algorithm is applied to Higashiyama ward, Kyoto, Japan. Owing to the information of building regions provided by segmentation, the modeling is successful even in dense urban areas. Therefore, the proposed algorithm is concluded to be effective in automatically generating building models in dense urban areas.