• DocumentCode
    739922
  • Title

    Canopy Density Model: A New ALS-Derived Product to Generate Multilayer Crown Cover Maps

  • Author

    Ferraz, Antonio ; Mallet, Clement ; Jacquemoud, Stephane ; Goncalves, Gil Rito ; Tome, Margarida ; Soares, Paula ; Pereira, Luisa Gomes ; Bretar, Frederic

  • Volume
    53
  • Issue
    12
  • fYear
    2015
  • Firstpage
    6776
  • Lastpage
    6790
  • Abstract
    The canopy density model (CDM), a new product interpolated from airborne laser scanner (ALS) data and dedicated to forest structure characterization is presented. It exploits both the multiecho capability of the ALS and a nonparametric density estimation technique called kernel density estimators (KDEs). The CDM is used to delineate the outmost perimeter of vegetation features and to compute forest crown cover (CrCO). Contrary to other works that focus on single-layer forest canopies, CrCo is derived here for each layer, namely, the overstory, the understory, and ground vegetation. The root-mean-square error of prediction determined by using field data acquired over 44 forest stands in a forest in Portugal allows the testing of the reliability of the method: It ranges from 6.21% (overstory) to 13.76% (ground vegetation). In addition, we investigate the ability of the CDM to map the CrCo for individual trees. Finally, two existing methods have been applied to our study site in order to assess improvements, advantages, and drawbacks of our approach.
  • Keywords
    Bandwidth; Estimation; Kernel; Probability density function; Three-dimensional displays; Vegetation; Vegetation mapping; Density estimation robust algorithm; forestry; lasers; probability density function; remote sensing; vegetation mapping;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2015.2448056
  • Filename
    7182762