Spectral Indices to Improve Crop Residue Cover Estimation under Varying Moisture Conditions

Crop 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...

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Main Authors: Miguel Quemada, Craig S. T. Daughtry
Format: Article
Language:English
Published: MDPI AG 2016-08-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/8/8/660
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author Miguel Quemada
Craig S. T. Daughtry
author_facet Miguel Quemada
Craig S. T. Daughtry
author_sort Miguel Quemada
collection DOAJ
description Crop 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.
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spelling doaj.art-4a8dd87db67948f78de9f353ef146a002022-12-22T04:08:53ZengMDPI AGRemote Sensing2072-42922016-08-018866010.3390/rs8080660rs8080660Spectral Indices to Improve Crop Residue Cover Estimation under Varying Moisture ConditionsMiguel Quemada0Craig S. T. Daughtry1School of Agricultural Engineering and CEIGRAM, Technical University of Madrid, Madrid 28040, SpainUSDA-ARS Hydrology and Remote Sensing Laboratory, 10300 Baltimore Ave., Beltsville, MD 20705, USACrop 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.http://www.mdpi.com/2072-4292/8/8/660cellulose absorption indexshortwave infrared normalized difference residue indexnormalized difference tillage indexspectral moisture indexwater content indices
spellingShingle Miguel Quemada
Craig S. T. Daughtry
Spectral Indices to Improve Crop Residue Cover Estimation under Varying Moisture Conditions
Remote Sensing
cellulose absorption index
shortwave infrared normalized difference residue index
normalized difference tillage index
spectral moisture index
water content indices
title Spectral Indices to Improve Crop Residue Cover Estimation under Varying Moisture Conditions
title_full Spectral Indices to Improve Crop Residue Cover Estimation under Varying Moisture Conditions
title_fullStr Spectral Indices to Improve Crop Residue Cover Estimation under Varying Moisture Conditions
title_full_unstemmed Spectral Indices to Improve Crop Residue Cover Estimation under Varying Moisture Conditions
title_short Spectral Indices to Improve Crop Residue Cover Estimation under Varying Moisture Conditions
title_sort spectral indices to improve crop residue cover estimation under varying moisture conditions
topic cellulose absorption index
shortwave infrared normalized difference residue index
normalized difference tillage index
spectral moisture index
water content indices
url http://www.mdpi.com/2072-4292/8/8/660
work_keys_str_mv AT miguelquemada spectralindicestoimprovecropresiduecoverestimationundervaryingmoistureconditions
AT craigstdaughtry spectralindicestoimprovecropresiduecoverestimationundervaryingmoistureconditions