Tree Species Classification Based on 3D Bark Texture Analysis

  • Ahlem Othmani
  • Alexandre Piboule
  • Oscar Dalmau
  • Nicolas Lomenie
  • Said Mokrani
  • Lew Fock Chong Lew Yan Voon
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8333)


Terrestrial Laser Scanning (TLS) technique is today widely used in ground plots to acquire 3D point clouds from which forest inventory attributes are calculated. In the case of mixed plantings where the 3D point clouds contain data from several different tree species, it is important to be able to automatically recognize the tree species in order to analyze the data of each of the species separately. Although automatic tree species recognition from TLS data is an important problem, it has received very little attention from the scientific community. In this paper we propose a method for classifying five different tree species using TLS data. Our method is based on the analysis of the 3D geometric texture of the bark in order to compute roughness measures and shape characteristics that are fed as input to a Random Forest classifier to classify the tree species. The method has been evaluated on a test set composed of 265 samples (53 samples of each of the 5 species) and the results obtained are very encouraging.


Tree species classification 3D pattern recognition 3D bark texture analysis forest inventory 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Ahlem Othmani
    • 1
    • 2
  • Alexandre Piboule
    • 2
  • Oscar Dalmau
    • 3
  • Nicolas Lomenie
    • 4
  • Said Mokrani
    • 1
  • Lew Fock Chong Lew Yan Voon
    • 1
  1. 1.Laboratory LE2I - UMR CNRS 6306Le CreusotFrance
  2. 2.Office National des Forêts, Pôle R&D de NancyNancyFrance
  3. 3.Centro de Investigacion en Matematicas A.CGuanajuatoMexico
  4. 4.Laboratory LIPADE - EA 2517Université Paris DescartesParisFrance

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