ARS | Publication request: Effects of soil composition and mineralogy on remote sesning of crop residue cover

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 18, 2008
Publication Date: N/A

Interpretive Summary: Recent trends in agriculture make use of conservation (no-till) methods, whereby farmers do not intensively plow fields. Conservation tillage typically maintain a significant portion of the soil remains covered with crop residues, which are the remnants (stalks, leaves, and unharvested cobs) of the previous season¿s crops. Crop residues are important for a number of reasons. Firstly, they help protect the soil from erosion by wind and water. Secondly, they act as a mulch to reduce evaporation of water from the soil. Thirdly, they decay to add carbon and nutrients to the soil and decrease the need for fertilizers. The addition of carbon to the soil also helps remove carbon dioxide from the atmosphere, and thus, reduce greenhouse gases. Since farmers can benefit from using conservation tillage by receiving subsidies and selling carbon credits, an efficient verification method becomes necessary. Remote sensing methods from aircraft and spacecraft can allow for rapid measurement of crop residue cover over many fields. These methods utilize the differences that crop residues have with soils in levels of reflected light (reflectance) in the shortwave infrared spectrum between 1900-2400 nm. However, soils have differing mineral and chemical compositions, and this affects reflectance, which could potentially complicate efforts to remotely measure crop residue cover. In order to assess crop residue cover we use two spectral indices, the Cellulose Absorption Index (CAI), and the Lignin-Cellulose Absorption (LCA) Index, that detect absorptions in spectra that are related to cellulose and lignin, two chemical compounds found in crop residues. All common soil minerals and compounds had much lower CAI values than crop residues, but that this was not always the case with LCA. Certain common soil minerals (e.g., calcite, dolomite, epidotes, chlorites) were greater than crop residues, which could complicate analyses. Soil organic carbon darkened soils and affected both CAI and LCA. Furthermore, LCA could not discriminate between live vegetation and dry crop residues, something which CAI is capable of. We also show that using soil mineralogical and soil carbon information we can potentially improve the accuracy of remotely sensed crop residue cover estimates.

Technical Abstract: The management of crop residues in agricultural fields influences soil erosion and soil carbon sequestration. Remote sensing methods can efficiently assess crop residue cover and tillaje intensity over many fields in a region. Although the reflectance spectra of soils and crop residues are often similar in the visible and near infrared (400 nm ¿ 1200 nm) wavelength region, specific diagnostic chemical absorption features are evident in the shortwave infrared (1200 nm ¿ 2500 nm) region. Two continuum-removal indices used for estimating residue cover are the Cellulose Absorption Index (CAI) and the Lignin-Cellulose Absorption (LCA) index, both of which use reflectances in the shortwave infrared. Soil mineralogy and composition will affect soil spectral properties and may limit the usefulness of these spectral indices in certain areas. Our objectives were to (1) evaluate the reflectance spectra of individual minerals and compounds found in soils for their potential effects on bare soil CAI and LCA values, and (2) show how these may be used to develop local calibrations of these indices. All common soil minerals had CAI values = 0.5, whereas crop residues were always > 0.5, allowing for good contrast between soils and residues. However, a number of common soil minerals had LCA values > 0.5, and, in some cases, the mineral LCA values were greater than crop residues, which could limit the effectiveness of LCA for residue cover estimation. The LCA of dry residues and live corn canopies were similar in value, unlike CAI, requiring that the Normalized Difference Vegetation Index (NDVI) or similar method be used to separate out green vegetation pixels. Mineral groups, such as garnets and chlorites, often have wide ranges in CAI and LCA values, and that mineralogical analyses often do not indentify individual mineral species required for precise CAI estimation, but that these would be useful in identifying soils requiring additional scrutiny.