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A Segmentation Method for Tree Crown Detection and Modelling from LiDAR Measurements

  • José Luis Silván-Cárdenas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7329)

Abstract

A watershed segmentation algorithm is proposed for automatic extraction of tree crowns from LiDAR data to support 3-d modelling of forest stands. A relatively sparse LiDAR point cloud was converted to a surface elevation in raster format and a canopy height model (CHM) extracted. Then, the segmentation method was applied on the CHM and results combined with the original point cloud to generate models of individual tree crowns. The method was tested in 200 circular plots (400 m 2) located over 50 sites of a conservation area in Mexico City. The segmentation method exhibited a moderate to perfect detection rate on 66% of plots tested. One major factor for a poor detection was identified as the relatively low sampling rate of LiDAR data with respect to crown sizes.

Keywords

Remote sensing LiDAR Watershed segmentation tree crown detection 3-d modelling 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • José Luis Silván-Cárdenas
    • 1
  1. 1.Centro de Investigación en Geografía y Geomática “Ing. Jorge L. Tamayo” A.C.TlalpanMexico

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