• DocumentCode
    1122142
  • Title

    An error and sensitivity analysis of the atmospheric- and soil-correcting variants of the NDVI for the MODIS-EOS

  • Author

    Huete, Alfred R. ; Liu, Hui Qing

  • Author_Institution
    Dept. of Soil & Water Sci., Arizona Univ., Tucson, AZ, USA
  • Volume
    32
  • Issue
    4
  • fYear
    1994
  • fDate
    7/1/1994 12:00:00 AM
  • Firstpage
    897
  • Lastpage
    905
  • Abstract
    Several soil- and atmospheric-correcting variants of the normalized difference vegetation index (NDVI) have been proposed to improve the accuracy in estimating biophysical plant parameters. In this study, a sensitivity analysis, utilizing simulated model data, was conducted on the NDVI and variants by analyzing the atmospheric- and soil-perturbed responses as a continuous function of leaf area index. Percent relative error and vegetation equivalent “noise” (VEN) were calculated for soil and atmospheric influences, separately and combined. The NDVI variants included the soil-adjusted vegetation index (SAVI), the atmospherically resistant vegetation index (ARVI), the soil-adjusted and atmospherically resistant vegetation index (SARVI), the modified SAVI (MSAVI), and modified SARVI (MSARVI). Soil and atmospheric error were of similar magnitudes, but varied with the vegetation index. All new variants outperformed the NDVI. The atmospherically resistant versions minimized atmospheric noise, but enhanced soil noise, while the soil adjusted variants minimized soil noise, but remained sensitive to the atmosphere. The SARVI, which had both a soil and atmosphere calibration term, performed the best with a relative error of 10 percent and VEN of ±0.33 LAI. By contrast, the NDM had a relative error of 20 percent and VEN of ±0.97 LAI
  • Keywords
    geophysical techniques; infrared imaging; remote sensing; ARVI; EOS; IR method; MODIS; NDVI; SARVI; SAVI; atmospheric correction; atmospherically resistant vegetation index; biophysical plant parameter; error analysis; geophysical measurement technique; leaf area index; normalized difference vegetation index; optical; remote sensing; sensitivity analysis; simulated model; soil-adjusted; soil-correcting variant; vegetation mapping; visible infrared; Analytical models; Atmosphere; Atmospheric modeling; Calibration; Equations; Immune system; Parameter estimation; Sensitivity analysis; Soil; Vegetation;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.298018
  • Filename
    298018