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This article in AJ

  1. Vol. 97 No. 3, p. 864-871
     
    Received: Nov 26, 2003
    Published: May, 2005


    * Corresponding author(s): cdaughtry@hydrolab.arsusda.gov
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doi:10.2134/agronj2003.0291

Remote Sensing the Spatial Distribution of Crop Residues

  1. C. S. T. Daughtry *,
  2. E. R. Hunt,
  3. P. C. Doraiswamy and
  4. J. E. McMurtrey
  1. USDA-ARS, Hydrol. and Remote Sens. Lab., Bldg. 007, Rm. 104, 10300 Baltimore Ave., Beltsville, MD 20705-2350 USA

Abstract

Management of plant litter or crop residues in agricultural fields is an important consideration for reducing soil erosion and increasing soil organic C. Current methods of quantifying crop residue cover are inadequate for characterizing the spatial variability of residue cover within fields and across large regions. Our objectives were to evaluate several spectral indices for measuring crop residue cover using ground-based and airborne hyperspectral data and to categorize soil tillage intensity in agricultural fields based on crop residue cover. Reflectance spectra of mixtures of crop residues, green vegetation, and soil were acquired over the 400- to 2500-nm wavelength region. High-altitude AVIRIS (Airborne Visible Infrared Imaging Spectrometer) data were also acquired near Beltsville, MD, in May 2000. Broad absorption features near 2100 and 2300 nm in the reflectance spectra of crop residues were associated with cellulose and lignin. These features were not evident in the spectra of green vegetation and soils. Crop residue cover was linearly related to the cellulose absorption index, which was defined as the relative depth of the 2100-nm absorption feature. Other spectral indices for crop residue were calculated and evaluated. The best spectral indices were based on relatively narrow (10–50 nm) bands in the 2000- to 2400-nm region, were linearly related to crop residue cover, and correctly identified tillage intensity classes in >90% of test agricultural fields. Regional surveys of soil management practices that affect soil conservation and soil C dynamics may be feasible using advanced multispectral or hyperspectral imaging systems.

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Copyright © 2005. American Society of AgronomyAmerican Society of Agronomy

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