The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLI-B3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 221–225, 2016
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 221–225, 2016

  09 Jun 2016

09 Jun 2016


H. Guan1, S. Cao1, Y. Yu2, J. Li3,4, N. Liu1, P. Chen1, and Y. Li5 H. Guan et al.
  • 1School of Geography and Remote Sensing, Nanjing University of Information Scienchaiye & Technology, Nanjing, 210044, China
  • 2Faculty of Computer and Software Engineering, Huaiyin Institute of Technology, Huaian, 223003, China
  • 3School of Information Science and Engineering, Xiamen University, Xiamen, Fujian 361005, China
  • 4Department of Geography and Environmental Management, University of Waterloo, Waterloo, ON N2L 3G1, Canada
  • 5School of Civil Engineering and Architecture, Nanchang University, Nanchang, 330031 China

Keywords: Mobile Laser Scanning Data, Filtering, Tree Extraction, Voxelization, Normalized Cut

Abstract. Our work addresses the problem of extracting trees from mobile laser scanning data. The work is a two step-wise strategy, including terrain point removal and tree segmentation. First, a voxel-based upward growing filtering is proposed to remove terrain points from the mobile laser scanning data. Then, a tree segmentation is presented to extract individual trees via a Euclidean distance clustering approach and Voxel-based Normalized Cut (VNCut) segmentation approach. A road section data acquired by a RIEGL VMX-450 system are selected for evaluating the proposed tree segmentation method. Qualitative analysis shows that our algorithm achieves a good performance.