Spectral Indices to Improve Crop Residue Cover Estimation under Varying Moisture Conditions
AbstractCrop residues on the soil surface protect the soil against erosion, increase water infiltration and reduce agrochemicals in runoff water. Crop residues and soils are spectrally different in the absorption features associated with cellulose and lignin. Our objectives were to: (1) assess the impact of water on the spectral indices for estimating crop residue cover (fR); (2) evaluate spectral water indices for estimating the relative water content (RWC) of crop residues and soils; and (3) propose methods that mitigate the uncertainty caused by variable moisture conditions on estimates of fR. Reflectance spectra of diverse crops and soils were acquired in the laboratory over the 400–2400-nm wavelength region. Using the laboratory data, a linear mixture model simulated the reflectance of scenes with various fR and levels of RWC. Additional reflectance spectra were acquired over agricultural fields with a wide range of crop residue covers and scene moisture conditions. Spectral indices for estimating crop residue cover that were evaluated in this study included the Normalized Difference Tillage Index (NDTI), the Shortwave Infrared Normalized Difference Residue Index (SINDRI) and the Cellulose Absorption Index (CAI). Multivariate linear models that used pairs of spectral indices—one for RWC and one for fR—significantly improved estimates of fR using CAI and SINDRI. For NDTI to reliably assess fR, scene RWC should be relatively dry (RWC < 0.25). These techniques provide the tools needed to monitor the spatial and temporal changes in crop residue cover and help determine where additional conservation practices may be required. View Full-Text
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Quemada, M.; Daughtry, C.S.T. Spectral Indices to Improve Crop Residue Cover Estimation under Varying Moisture Conditions. Remote Sens. 2016, 8, 660.
Quemada M, Daughtry CST. Spectral Indices to Improve Crop Residue Cover Estimation under Varying Moisture Conditions. Remote Sensing. 2016; 8(8):660.Chicago/Turabian Style
Quemada, Miguel; Daughtry, Craig S.T. 2016. "Spectral Indices to Improve Crop Residue Cover Estimation under Varying Moisture Conditions." Remote Sens. 8, no. 8: 660.
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