Abstract
Abstract. Over the last 20 years the use of, and demand for, three dimensional (3D) building models has meant there has been a vast amount of research conducted in automating the extraction and reconstruction of these models from airborne sensors. Whilst many different approaches have been suggested, full automation is yet to be achieved and research has suggested that the combination of data from multiple sources is required in order to achieve this. Developments in digital photogrammetry have delivered improvements in spatial resolution whilst higher image overlap to increase the number of pixel correspondents between images, giving the name multi-ray photogrammetry, has improved the resolution and quality of its by-products. In this paper the extraction of roof geometry from multiray photogrammetry will be covered, which underpins 3D building reconstruction. Using orthophotos, roof vertices are extracted using the Canny edge detector. Roof planes are detected from digital surface models (DSM) by extracting information from 2D cross sections and measuring height differences. To eliminate overhanging vegetation, the segmentation of trees is investigated by calculating the characteristics of a point within a local neighbourhood of the photogrammetric point cloud. The results highlight the complementary nature of these information sources, and a methodology for integration and reconstruction of roof geometry is proposed.
Highlights
The use of and demand for three dimensional (3D) building models has grown significantly over the last twenty years for numerous different uses
It is fairly straightforward to automate the procedure for the reconstruction of LOD1 building models, which presumes the roof of all buildings to be flat
LOD3 and LOD4 are beyond the scope of this research and require extra information such as oblique imagery or terrestrial data to create LOD3 and internal building geometry for LOD4
Summary
The use of and demand for three dimensional (3D) building models has grown significantly over the last twenty years for numerous different uses. The manual reconstruction of buildings from aerial imagery via stereoscopy or from lidar data is a time consuming and laborious task, the automation of the extraction and reconstruction of 3D buildings has been a major research focus. Research has exploited both aerial imagery and lidar data for the reconstruction of 3D models at varying levels of detail. In order to reconstruct a more faithful roof type and create a LOD2 building model, the process is much harder to automate, and requires the extraction of detailed 3D building geometry. LOD3 and LOD4 are beyond the scope of this research and require extra information such as oblique imagery or terrestrial data to create LOD3 and internal building geometry for LOD4
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