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Front Earth Sci    2011, Vol. 5 Issue (3) : 229-238    https://doi.org/10.1007/s11707-011-0175-0
REVIEW ARTICLE
Remote sensing of soil properties in precision agriculture: A review
Yufeng GE1, J. Alex THOMASSON1, Ruixiu SUI2()
1. Department of Biological and Agriculture Engineering, Texas A&M University, College Station, TX 77843-2117, USA; 2. USDA-ARS, Crop Production Systems Research Unit, Stoneville, MS 38776, USA
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Abstract

The success of precision agriculture (PA) depends strongly upon an efficient and accurate method for in-field soil property determination. This information is critical for farmers to calculate the proper amount of inputs for best crop performance and least environmental effect. Grid sampling, as a traditional way to explore in-field soil variation, is no longer considered appropriate since it is labor intensive, time consuming and lacks spatial exhaustiveness. Remote sensing (RS) provides a new tool for PA information gathering and has advantages of low cost, rapidity, and relatively high spatial resolution. Great progress has been made in utilizing RS for in-field soil property determination. In this article, recent publications on the subject of RS of soil properties in PA are reviewed. It was found that a large array of agriculturally-important soil properties (including textures, organic and inorganic carbon content, macro- and micro-nutrients, moisture content, cation exchange capacity, electrical conductivity, pH, and iron) were quantified with RS successfully to the various extents. The applications varied from laboratory-analysis of soil samples with a bench-top spectrometer to field-scale soil mapping with satellite hyper-spectral imagery. The visible and near-infrared regions are most commonly used to infer soil properties, with the ultraviolet, mid-infrared, and thermal-infrared regions have been used occasionally. In terms of data analysis, MLR, PCR, and PLSR are three techniques most widely used. Limitations and possibilities of using RS for agricultural soil property characterization were also identified in this article.
Keywords soil      soil property      precision agriculture (PA)      remote sensing (RS)      near-infrared reflectance spectroscopy      sensor     
Corresponding Author(s): SUI Ruixiu,Email:ruixiu.sui@ars.usda.gov   
Issue Date: 05 September 2011
 Cite this article:   
Yufeng GE,J. Alex THOMASSON,Ruixiu SUI. Remote sensing of soil properties in precision agriculture: A review[J]. Front Earth Sci, 2011, 5(3): 229-238.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-011-0175-0
https://academic.hep.com.cn/fesci/EN/Y2011/V5/I3/229
YearAuthorSoil properties §
PKCaMgZnNaNpHOMECCECClaySiltSandMCOthers
1986Dalal and Henry××Organic C
1991Coleman et al.××××
Morra et al.×Total C
1993Abdel-Hamid××××CaCO3, Fe, salt
Coleman et al.××××Iron oxide
Sudduth and Hummel×××
1995Ben-Dor and Banin×××CaCO3
Coleman and Tadesse××××
1996Hummel et al.××
1998Palicios-Orueta et al.××××Iron content
1999Ehsani et al.×
GopalaPillai and TianSoil type
Malley et al.×××××××S, Mn, Fe
Varvel et al.××
2000Barnes and Baker×××
2001Chang et al.×××××××××××××
Ehsani et al.×
Hummel et al.××
Merry and Janik×××××××
Thomasson et al.×××××××××
Slaughter et al.×
2002Kaleita and Tian××
Lobell and Asner×
2003Cozzolino and Moron××××××Mn, Fe
Hutchinson×
Kaleita et al.×
Lee et al.××××××
Leon et al.××××××××
Stangeland et al.××××××Buffer pH
2004Bogrekci et al.×
2005Bogrekci and Lee (a)×
Bogrekci and Lee (b)××××
Bajwa and Tian×××××××
Stamatiadis et al.×××××××××
2006Ge and Thomasson××××××××
2007Waiser et al.×
Tab.1  Summary of information reported for remote sensing of soil properties in precision agriculture on soil chemical, physical, and other properties
Author & YearSensing technique
Sensing platform ?Sensor type §Waveband ?
SatelliteAerialLaboratoryFieldMultiHyperUVVISNIRMIRTHMW
Dalal and Henry, 1986×××
Agbu et al., 1990××××
Coleman et al., 1991××××××
Morra et al., 1991×××
Coleman et al., 1993××××××
Sudduth and Hummel, 1993a×××
Ben-Dor and Banin, 1994××××
Ben-Dor and Banin, 1995×××
Coleman and Tadesse, 1995×××
Hummel et al., 1996××××
Galvdo et al., 1997×××××
Palacios-Orueta and Ustin, 1998×××××
Ehsani et al., 1999×××
GopalaPillai and Tian, 1999××××
Malley et al., 1999××××
Varvel et al., 1999××××
Barnes and Baker, 2000××××××
Chang et al., 2001×××
Ehsani et al., 2001×××
Hummel et al., 2001×××
Slaughter et al., 2001××××
Thomasson et al., 2001a××××
Thomasson et al., 2001b××××××
Cozzolino and Moron, 2003××××
Hutchinson 2003××
Lee et al., 2003××××
Leon et al., 2003××××
Odhiambo et al., 2003××
Stangeland et al., 2003××××
Bajwa and Tian, 2005××××
Bogrekci and Lee, 2005a×××××
Bogrekci and Lee, 2005b×××××
Stamatiadis et al., 2005××××
Kaleita et al., 2005××××
Sullivan et al., 2005×××
Ge and Thomasson, 2006××××
Waiser et al., 2007××××
Tab.2  Summary of information reported for remote sensing of soil properties in precision agriculture on sensing platforms, sensor types, and wavebands.
Author & YearData analysis technique
Preprocessing ?Qualitative ?Quantitative §
Dalal and Henry, 1986MLR
Frazier and Cheng, 1989BR
Agbu et al., 1990BRMLR
Coleman et al., 1991DISCMLR
Morra et al., 1991DerivativeMLR
Coleman et al., 1993DISCMLR
Sudduth and Hummel, 1993aAveragingMLR, PCR, PLS
Ben-Dor and Banin, 1994Averaging, derivativeMLR
Ben-Dor and Banin, 1995Averaging, derivativeMLR
Coleman and Tadesse, 1995DISCMLR
Hummel et al., 1996MLR, PLS
Galvdo, et al., 1997BRPCA, MLR
Palacios-Orueta and Ustin, 1998AveragingCDABD, PCA
Ehsani et al. 1999PCR, PLS
GopalaPillai and Tian, 1999UnCls
Malley et al., 1999Averaging, derivativeMLR
Varvel et al., 1999CORR
Barnes and Baker, 2000UnCls, SuCls
Chang et al., 2001Averaging, derivativePCR
Ehsani et al., 2001SG, FFT, waveletBRCORR
Hummel et al., 2001MLR
Slaughter et al., 2001PLS
Thomasson et al., 2001aAveragingMLR
Cozzolino and Moron, 2003Averaging, derivativePLS
Lee et al., 2003PLS
Leon et al., 2003BRPCA, MLR
Odhiambo et al., 2003F-NN
Stangeland et al., 2003Averaging, derivativePLS
Bajwa and Tian, 2005DerivativePLS
Bogrekci and Lee, 2005aSG, derivativeBR, DISCMLR, PLS
Bogrekci and Lee, 2005bSG, derivativeDISCPCA, MLR, PLS
Stamatiadis et al., 2005BRMLR
Kaleita et al., 2005K-mean smoothingPLS
Ge and Thomasson, 2006WaveletMLR
Waiser et al., 2007Averaging, derivativePLS
Tab.3  Summary of information reported for remote sensing of soil properties in precision agriculture on data analysis techniques.
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