• DocumentCode
    1444068
  • Title

    Angular and seasonal variation of spectral surface reflectance ratios: implications for the remote sensing of aerosol over land

  • Author

    Remer, Lorraine A. ; Wald, Andrew E. ; Kaufman, Yoram J.

  • Author_Institution
    Lab. for Atmos., NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • Volume
    39
  • Issue
    2
  • fYear
    2001
  • fDate
    2/1/2001 12:00:00 AM
  • Firstpage
    275
  • Lastpage
    283
  • Abstract
    We obtain valuable information on the angular and seasonal variability of surface reflectance using a hand-held spectrometer from a light aircraft. The data is used to test a procedure that allows us to estimate visible surface reflectance from the longer wavelength 2.1 μm channel (mid-IR). Estimating or avoiding surface reflectance in the visible is a vital first step in most algorithms that retrieve aerosol optical thickness over land targets. The data indicate that specular reflection found when viewing targets from the forward direction can severely corrupt the relationships between the visible and 2.1 μm reflectance that were derived from nadir data. There is a month by month variation in the ratios between the visible and the mid-IR, weakly correlated to the Normalized Difference Vegetation Index (NDVI). If specular reflection is not avoided, the errors resulting from estimating surface reflectance from the mid-IR exceed the acceptable limit of Δρ~0.01 in roughly 40% of the cases, using the current algorithm. This is reduced to 25% of the cases if specular reflection is avoided
  • Keywords
    aerosols; albedo; remote sensing; 2.1 mum; NDVI; Normalized Difference Vegetation Index; aerosol; aerosol optical thickness; angular variation; nadir data; remote sensing; seasonal variation; spectral surface reflectance ratios; specular reflection; surface reflectance; visible surface reflectance; Aerosols; Aircraft; Land surface; Optical reflection; Optical surface waves; Reflectivity; Spectroscopy; Surface waves; Testing; Vegetation;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.905235
  • Filename
    905235