Volume II-3/W4
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W4, 189-196, 2015
https://doi.org/10.5194/isprsannals-II-3-W4-189-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., II-3/W4, 189-196, 2015
https://doi.org/10.5194/isprsannals-II-3-W4-189-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  11 Mar 2015

11 Mar 2015

MASSIVE-SCALE TREE MODELLING FROM TLS DATA

P. Raumonen1, E. Casella2, K. Calders3, S. Murphy4, M. Åkerblom1, and M. Kaasalainen1 P. Raumonen et al.
  • 1Tampere University of Technology, Tampere, Finland
  • 2Forest Research, Farnham, UK
  • 3Wageningen University, Wageningen, Netherlands
  • 4Melbourne School of Land and Environment, University of Melbourne, Australia

Keywords: Quantitative structure models, automatic tree extraction, biomass, forest plot, ground truth, oak, eucalyptus, LiDAR

Abstract. This paper presents a method for reconstructing automatically the quantitative structure model of every tree in a forest plot from terrestrial laser scanner data. A new feature is the automatic extraction of individual trees from the point cloud. The method is tested with a 30-m diameter English oak plot and a 80-m diameter Australian eucalyptus plot. For the oak plot the total biomass was overestimated by about 17 %, when compared to allometry (N = 15), and the modelling time was about 100 min with a laptop. For the eucalyptus plot the total biomass was overestimated by about 8.5 %, when compared to a destructive reference (N = 27), and the modelling time was about 160 min. The method provides accurate and fast tree modelling abilities for, e.g., biomass estimation and ground truth data for airborne measurements at a massive ground scale.