Next Article in Journal
Previous Article in Journal
Remote Sens. 2014, 6(5), 3716-3751; doi:10.3390/rs6053716
Article

Automatic Segmentation of Raw LIDAR Data for Extraction of Building Roofs

1,*  and 2
Received: 15 January 2014; in revised form: 3 April 2014 / Accepted: 9 April 2014 / Published: 28 April 2014
View Full-Text   |   Download PDF [22754 KB, uploaded 19 June 2014]   |   Browse Figures
Abstract: Automatic extraction of building roofs from remote sensing data is important for many applications, including 3D city modeling. This paper proposes a new method for automatic segmentation of raw LIDAR (light detection and ranging) data. 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 form a “building mask”. The second group contains non-ground points that are clustered using the building mask. A cluster of points usually represents an individual building or tree. During segmentation, the planar roof segments are extracted from each cluster of points and refined using rules, such as the coplanarity of points and their locality. Planes on trees are removed using information, such as area and point height difference. Experimental results on nine areas of six different data sets show that the proposed method can successfully remove vegetation and, so, offers a high success rate for building detection (about 90% correctness and completeness) and roof plane extraction (about 80% correctness and completeness), when LIDAR point density is as low as four points/m2. Thus, the proposed method can be exploited in various applications.
Keywords: LIDAR; point cloud; segmentation; automatic; building; roof; extraction LIDAR; point cloud; segmentation; automatic; building; roof; extraction
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Export to BibTeX |
EndNote


MDPI and ACS Style

Awrangjeb, M.; Fraser, C.S. Automatic Segmentation of Raw LIDAR Data for Extraction of Building Roofs. Remote Sens. 2014, 6, 3716-3751.

AMA Style

Awrangjeb M, Fraser CS. Automatic Segmentation of Raw LIDAR Data for Extraction of Building Roofs. Remote Sensing. 2014; 6(5):3716-3751.

Chicago/Turabian Style

Awrangjeb, Mohammad; Fraser, Clive S. 2014. "Automatic Segmentation of Raw LIDAR Data for Extraction of Building Roofs." Remote Sens. 6, no. 5: 3716-3751.


Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert