• DocumentCode
    767909
  • Title

    A feedback based modification of the NDVI to minimize canopy background and atmospheric noise

  • Author

    Hui qing Liu ; Huete, Alfredo

  • Author_Institution
    Dept. of Soil & Water Sci., Arizona Univ., Tucson, AZ
  • Volume
    33
  • Issue
    2
  • fYear
    1995
  • fDate
    3/1/1995 12:00:00 AM
  • Firstpage
    457
  • Lastpage
    465
  • Abstract
    The Normalized Difference Vegetation Index (NDVI) equation has a simple, open loop structure (no feedback), which renders it susceptible to large sources of error and uncertainty over variable atmospheric and canopy background conditions. In this study, a systems analysis approach is used to examine noise sources in existing vegetation indices (VIs) and to develop a stable, modified NDVI (MNDVI) equation. The MNDVI, a closed-loop version of the NDVI, was constructed by adding 1) a soil and atmospheric noise feedback loop, and 2) an atmospheric noise compensation forward loop. The coefficients developed for the MNDVI are physically-based and are empirically related to the expected range of atmospheric and background “boundary” conditions. The MNDVI can be used with data uncorrected for atmosphere, as well as with Rayleigh corrected and atmospherically corrected data. In the field observational and simulated data sets tested, the MNDVI was found to considerably reduce noise for any complex soil and atmospheric situation. The resulting uncertainty, expressed as vegetation equivalent noise, was ±0.11 leaf area index (LAI) units, which was 7 times less than encountered with the NDVI (±0.8 LAI). These results indicate that the MNDVI may be satisfactory in meeting the need for accurate, long term vegetation measurements for the Earth Observing System (EOS) program
  • Keywords
    geophysical techniques; infrared imaging; remote sensing; IR scattering; LAI; NDVI; Normalized Difference Vegetation Index; atmospheric noise; boundary conditions; canopy background; compensation forward loop; feedback based modification; geophysical; leaf area index; measurement technique; minimization; modified equation; noise source; optical visible light reflection; remote sensing; systems analysis approach; vegetation mapping; Atmosphere; Atmospheric modeling; Difference equations; Earth Observing System; Feedback loop; Noise reduction; Soil; Testing; Uncertainty; Vegetation;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/36.377946
  • Filename
    377946