• DocumentCode
    1177817
  • Title

    Measurement of canopy geometry characteristics using LiDAR laser altimetry: a feasibility study

  • Author

    Houldcroft, Caroline J. ; Campbell, Claire L. ; Davenport, Ian J. ; Gurney, Robert J. ; Holden, Nick

  • Author_Institution
    Climate Land Surface Syst. Interaction Centre, Univ. of Wales, Swansea, UK
  • Volume
    43
  • Issue
    10
  • fYear
    2005
  • Firstpage
    2270
  • Lastpage
    2282
  • Abstract
    Airborne scanning laser altimetry offers the potential for extracting high-resolution vegetation structure characteristics for monitoring and modeling the land surface. A unique dataset is used to study the sensitivity of laser interception profiles and laser-derived leaf area index (LAI) to assumptions about the surface structure and the measurement process. To simulate laser interception, one- and three-dimensional (3-D) vegetation structure models have been developed for maize and sunflower crops. Over sunflowers, a simple regression technique has been developed to extract laser-derived LAI, which accounts for measurement and model biases. Over maize, a 3-D structure/interception model that accounts for the effects of the laser inclination angle and detection threshold has enabled the fraction of radiation reaching the ground surface to be modelled to within 0.5% of the observed fraction. Good agreement was found between modelled and measured profiles of laser interception with a vertical resolution of 10 cm.
  • Keywords
    crops; remote sensing by laser beam; vegetation mapping; 3D vegetation structure; LiDAR laser altimetry; airborne scanning laser altimetry; canopy geometry characteristics; canopy height; detection threshold; laser inclination angle; laser interception profiles; leaf area index; maize crops; remote sensing; sunflower crops; vegetation mapping; Area measurement; Crops; Geometrical optics; Land surface; Laser modes; Laser radar; Monitoring; Surface emitting lasers; Surface structures; Vegetation; Canopy height; leaf area index (LAI); 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.2005.856639
  • Filename
    1512398