• DocumentCode
    2114927
  • Title

    Retrieval of surface reflectance and LAI mapping with data from ALI, Hyperion and AVIRIS

  • Author

    Pu, R. ; Gong, P. ; Biging, G. ; Larrieu, M.R.

  • Author_Institution
    Center for Assessment & Monitoring of Forest & Environ. Resources, California Univ., Berkeley, CA, USA
  • Volume
    3
  • fYear
    2002
  • fDate
    24-28 June 2002
  • Firstpage
    1411
  • Abstract
    Data acquired with Advanced Land Imager (ALI), Hyperspectral Imager (Hyperion) and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), were used to estimate and map forest LAI. Analysis methods include 1) simulating the total at-sensor radiances using MODTRAN4, 2) modifying retrieved surface reflectance with ground spectroradiometric measurements, 3) constructing 6-term LAI prediction models to predict pixel-based LAI, and 4) mapping LAI. The experimental results indicate that the retrieval of surface reflectance is the most successful with AVIRIS, followed by Hyperion and ALI. AVIRIS data can produce more reasonable LAI map than the other two sensors. The results also indicate that Hyperion data have potentially extensive application values in bio-parameter extraction at varied scales.
  • Keywords
    forestry; geophysical techniques; vegetation mapping; ALI; AVIRIS; Advanced Land Imager; Argentina; Hyperion; Hyperspectral Imager; LAI; MODTRAN4; forest; geophysical measurement technique; hyperspectral remote sensing; leaf area index; multispectral remote sensing; pine trees; surface reflectance; vegetation mapping; Analytical models; Hyperspectral imaging; Hyperspectral sensors; Information retrieval; Infrared imaging; Infrared spectra; Predictive models; Reflectivity; Spectroradiometers; Spectroscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
  • Print_ISBN
    0-7803-7536-X
  • Type

    conf

  • DOI
    10.1109/IGARSS.2002.1026133
  • Filename
    1026133