ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume II-5/W2
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5/W2, 115–120, 2013
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-5/W2, 115–120, 2013

  16 Oct 2013

16 Oct 2013

Voxel tree modeling for estimating leaf area density and woody material volume using 3-D LIDAR data

F. Hosoi, Y. Nakai, and K. Omasa F. Hosoi et al.
  • Graduate School of Agricultural and Life Sciences, The University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo 113-8657, Japan

Keywords: Broad leaf, Leaf area density, Lidar, Point cloud, 3D, Voxel model, Woody material volume

Abstract. In this work, the main focus is on voxel tree modeling using 3-D lidar data for accurate leaf area density (LAD) and woody material volume estimation. For more accurate LAD estimation, the voxel model was constructed by combining airborne and portable ground-based lidar data. The profiles obtained by the two types of lidar complemented each other, thus eliminating blind regions and yielding more accurate LAD profiles than could be obtained by using each type of lidar alone. Parts of the LAD profiles that were underestimated even when data from both lidars were combined were interpolated by using a Gaussian function, yielding improved results. A laser beam coverage index, Ω, incorporating the lidar's laser beam settings and a laser beam attenuation factor, was proposed. This index showed general applicability to explain the LAD estimation error for LAD measurements using different types of lidars. In addition, we proposed a method for accurate woody material volume estimation based on a 3-D voxel-based solid modeling of the tree from portable scanning lidar data. The solid model was composed of consecutive voxels that filled the outer surface and the interior of the stem and large branches. By using the model, the woody material volume of not only the whole target tree but also of any part of the target tree can be directly calculated easily and accurately by counting the number of corresponding voxels and multiplying the result by the per-voxel volume.