• J. Massey
• M. Cox
• S. Oppenheimer
• M. Razzaghi
• W. Kingery

Determination of soil surface properties is vital for the management of natural resources under an array of contexts. Soil-related information are needed to improve (a) agricultural efficiency/productivity through precision agriculture, (b) the estimation/mitigation of non-point source pollution, (c) the verification of regulatory compliance with various conservation programs, and (d) the measurement of temporal changes in soils for global climate modeling. Field sampling of soils to determine soil surface properties is costly, time consuming and must be conducted each time that new information is required. Devising techniques to remotely sense soil surface properties would allow the economic and environmental benefits of precision agriculture to be more fully realized.

1. Determine techniques that couple recent advances in hyperspectral remote sensing techniques with knowledge of soil genesis and morphology to delineate soil management zones,
2. Use NIR cellulose-lignin absorbance indices and color to detect and quantify crop residues on agronomic soil surfaces, and
3. Determine mathematical corrections for light quality effects on soil and crop reflectance values collected under "less than ideal" light conditions.

Initial research will focus on the detection and quantification of crop residues on soil surfaces. This work will involve the following procedures:

1. Build spectral libraries of "pure" crop residues (wheat, corn, cotton, soybean) to determine (a) spectral differences between residues, (b) change in spectral response with moisture content (c) change in spectral response over time as crop residue ages and (d) spectral response under "less than ideal" lighting conditions.

1. Build spectral libraries of crop residues in field trials having known levels of crop residue. These residue levels will be operationally defined (i.e., residue remaining after one pass of disc per standard tillage practices).
2. Determine spectral response change over time as crop residue ages. Additional factors to address include soil moisture and surface roughness.

Field treatments will include (a) residue remaining after harvest, (b) untilled soil with residues removed, (c) bare, tilled soil, and residues remaining after (d) one, (e) two or three (f) tillage pass. Surface residues will be quantified using linear transect method and other techniques as appropriate. Plots are to be maintained in a weed-free condition.

1. Determine utility of published cellulose absorption indices based on cellulose and lignin contents to detect and provide quantitative estimate of residue cover.
2. Devise light-quality algorithm to predict "ideal" reflectance from crop residue obtained under "less than ideal" lighting conditions.