Automatic extraction of building roofs using LIDAR data and multispectral imagery

作者：Awrangjeb Mohammad^*; Zhang Chunsun; Fraser Clive S

来源：ISPRS Journal of Photogrammetry and Remote Sensing, 2013, 83: 1-18.

DOI：10.1016/j.isprsjprs.2013.05.006

• Building
• Feature
• Extraction
• Reconstruction
• Automation
• Integration
• LIDAR
• Orthoimage

Automatic 3D extraction of building roofs from remotely sensed data is important for many applications including city modelling. This paper proposes a new method for automatic 3D roof extraction through an effective integration of LIDAR (Light Detection And Ranging) data and multispectral orthoimagery. Using the ground height from a DEM (Digital Elevation Model), the raw LIDAR points are separated into two groups. The first group contains the ground points that are exploited to constitute a %26apos;ground mask%26apos;. The second group contains the non-ground points which are segmented using an innovative image line guided segmentation technique to extract the roof planes. The image lines are extracted from the grey-scale version of the orthoimage and then classified into several classes such as %26apos;ground%26apos;, %26apos;tree%26apos;, %26apos;roof edge%26apos; and %26apos;roof ridge%26apos; using the ground mask and colour and texture information from the orthoimagery. During segmentation of the non-ground LIDAR points, the lines from the latter two classes are used as baselines to locate the nearby LIDAR points of the neighbouring planes. For each plane a robust seed region is thereby defined using the nearby non-ground LIDAR points of a baseline and this region is iteratively grown to extract the complete roof plane. Finally, a newly proposed rule-based procedure is applied to remove planes constructed on trees. Experimental results show that the proposed method can successfully remove vegetation and so offers high extraction rates.

• 出版日期2013-9