• DocumentCode
    762443
  • Title

    Refined empirical line approach for retrieving surface reflectance from EO-1 ALI images

  • Author

    Moran, M. Susan ; Bryant, Ross ; Holifield, Chandra D. ; McElroy, Stephen

  • Author_Institution
    ARS Southwest Watershed Res. Center, U.S. Dept. of Agric., Tucson, AZ, USA
  • Volume
    41
  • Issue
    6
  • fYear
    2003
  • fDate
    6/1/2003 12:00:00 AM
  • Firstpage
    1411
  • Lastpage
    1414
  • Abstract
    The refined empirical line (REL) approach was used to convert the Earth Observing 1 (EO-1) Advanced Land Imager (ALI) sensor digital number (dn) to surface spectral reflectance (ρλ). The dn-to-ρλ relation was derived from a bright target of known reflectance in the image, and the modeled estimates of the image dn at ρλ=0. The mean absolute percent difference (Δ%) between ρλ retrieved from ALI using the REL approach and ground-measured ρλ for 15 targets on six dates were 42%, 6%, and 13% in the ALI visible, near-infrared (NIR), and shortwave infrared (SWIR) spectral bands, respectively. The Δ% for ρλ retrieved from ALI without any atmospheric correction were 155%, 9%, and 10% for visible, NIR, and SWIR bands, respectively. For the clear, dry atmospheric conditions in Arizona, REL correction was most crucial for the dark targets in the visible bands. Given the published values of an ALI dn for ρλ=0, the REL offers a simple approach for retrieving reflectance from multiple ALI images for temporal surface analysis.
  • Keywords
    geophysical signal processing; image processing; terrain mapping; Arizona; EO 1 ALI images; Earth Observing 1 Advanced Land Imager data; REL approach; image processing; refined empirical line approach; remote sensing; sensor digital number; spectral reflectance; surface reflectance; Atmospheric measurements; Earth; Image analysis; Image converters; Image retrieval; Image sensors; Infrared spectra; Reflectivity; Remote sensing; Satellites;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2003.813207
  • Filename
    1220249