Removing Moisture Effect on Soil Reflectance Properties: A Case Study of Clay Content Prediction
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摘要
Visible, near-infrared and shortwave-infrared(VNIR-SWIR) spectroscopy is an efficient approach for predicting soil properties because it reduces the time and cost of analyses. However, its advantages are hampered by the presence of soil moisture, which masks the major spectral absorptions of the soil and distorts the overall spectral shape. Hence, developing a procedure that skips the drying process for soil properties assessment directly from wet soil samples could save invaluable time. The goal of this study was twofold:proposing two approaches, partial least squares(PLS) and nearest neighbor spectral correction(NNSC), for dry spectral prediction and utilizing those spectra to demonstrate the ability to predict soil clay content. For these purposes, we measured 830 samples taken from eight common soil types in Israel that were sampled at 66 different locations. The dry spectrum accuracy was measured using the spectral angle mapper(SAM) and the average sum of deviations squared(ASDS), which resulted in low prediction errors of less than 8% and 14%, respectively. Later, our hypothesis was tested using the predicted dry soil spectra to predict the clay content, which resulted in R~2 of 0.69 and 0.58 in the PLS and NNSC methods, respectively. Finally, our results were compared to those obtained by external parameter orthogonalization(EPO) and direct standardization(DS). This study demonstrates the ability to evaluate the dry spectral fingerprint of a wet soil sample, which can be utilized in various pedological aspects such as soil monitoring, soil classification,and soil properties assessment.
Visible, near-infrared and shortwave-infrared(VNIR-SWIR) spectroscopy is an efficient approach for predicting soil properties because it reduces the time and cost of analyses. However, its advantages are hampered by the presence of soil moisture, which masks the major spectral absorptions of the soil and distorts the overall spectral shape. Hence, developing a procedure that skips the drying process for soil properties assessment directly from wet soil samples could save invaluable time. The goal of this study was twofold:proposing two approaches, partial least squares(PLS) and nearest neighbor spectral correction(NNSC), for dry spectral prediction and utilizing those spectra to demonstrate the ability to predict soil clay content. For these purposes, we measured 830 samples taken from eight common soil types in Israel that were sampled at 66 different locations. The dry spectrum accuracy was measured using the spectral angle mapper(SAM) and the average sum of deviations squared(ASDS), which resulted in low prediction errors of less than 8% and 14%, respectively. Later, our hypothesis was tested using the predicted dry soil spectra to predict the clay content, which resulted in R~2 of 0.69 and 0.58 in the PLS and NNSC methods, respectively. Finally, our results were compared to those obtained by external parameter orthogonalization(EPO) and direct standardization(DS). This study demonstrates the ability to evaluate the dry spectral fingerprint of a wet soil sample, which can be utilized in various pedological aspects such as soil monitoring, soil classification,and soil properties assessment.
Visible, near-infrared and shortwave-infrared(VNIR-SWIR) spectroscopy is an efficient approach for predicting soil properties because it reduces the time and cost of analyses. However, its advantages are hampered by the presence of soil moisture, which masks the major spectral absorptions of the soil and distorts the overall spectral shape. Hence, developing a procedure that skips the drying process for soil properties assessment directly from wet soil samples could save invaluable time. The goal of this study was twofold:proposing two approaches, partial least squares(PLS) and nearest neighbor spectral correction(NNSC), for dry spectral prediction and utilizing those spectra to demonstrate the ability to predict soil clay content. For these purposes, we measured 830 samples taken from eight common soil types in Israel that were sampled at 66 different locations. The dry spectrum accuracy was measured using the spectral angle mapper(SAM) and the average sum of deviations squared(ASDS), which resulted in low prediction errors of less than 8% and 14%, respectively. Later, our hypothesis was tested using the predicted dry soil spectra to predict the clay content, which resulted in R~2 of 0.69 and 0.58 in the PLS and NNSC methods, respectively. Finally, our results were compared to those obtained by external parameter orthogonalization(EPO) and direct standardization(DS). This study demonstrates the ability to evaluate the dry spectral fingerprint of a wet soil sample, which can be utilized in various pedological aspects such as soil monitoring, soil classification,and soil properties assessment.
引文
Ackerson J P,Demattê J A M,Morgan C L S.2015.Predicting clay content on field-moist intact tropical soils using a dried,ground VisNIR library with external parameter orthogonalization.Geoderma.259-260:196-204.
Arslan H,Tasan M,Yildirim D,Koksal E S,Cemek B.2014.Predicting field capacity,wilting point,and the other physical properties of soils using hyperspectral reflectance spectroscopy:Two different statistical approaches.Environ Monit Assess.186:5077-5088.
Banin A,Amiel A.1970.A correlative study of the chemical and physical properties of a group of natural soils of Israel.Geoderma.3:185-198.
Ben-Dor E,Banin A.1995.Near-infrared analysis as a rapid method to simultaneously evaluate several soil properties.Soil Sci Soc Am J.59:364-372.
Ben-Dor E,Kindel B,Goetz A F H.2004.Quality assessment of several methods to recover surface reflectance using synthetic imaging spectroscopy data.Remote Sens Environ.90:389-404.
Castaldi F,Chabrillat S,Jones A,Vreys K,Bomans B,van Wesemael B.2018.Soil organic carbon estimation in croplands by hyperspectral remote APEX data using the LUCAS topsoil database.Remote Sens.10:153.
Castaldi F,Palombo A,Pascucci S,Pignatti S,Santini F,Casa R.2015.Reducing the influence of soil moisture on the estimation of clay from hyperspectral data:a case study using simulated PRISMA data.Remote Sens.7:15561-15582.
Chabrillat S,Ben-Dor E,Viscarra Rossel R A,Demattê J A M.2013.Quantitative soil spectroscopy.Appl Environ Soil Sci.2013:616578.
Chabrillat S,Goetz A F H,Krosley L,Olsen H W.2002.Use of hyperspectral images in the identification and mapping of expansive clay soils and the role of spatial resolution.Remote Sens Environ.82:431-445.
Chang C W,Laird D A,Mausbach M J,Hurburgh Jr C R.2001.Near-infrared reflectance spectroscopy-principal components regression analyses of soil properties.Soil Sci Soc Am J.65:480-490.
Christy C D.2008.Real-time measurement of soil attributes using on-the-go near infrared reflectance spectroscopy.Comput Electron Agric.61:10-19.
Clark R N.1999.Spectroscopy of rocks and minerals,and principles of spectroscopy.In Rencz A N(ed.)Manual of Remote Sensing,Vol.3,Remote Sensing for the Earth Sciences.John Wiley and Sons,New York.pp.3-58.
Cohen M J,Prenger J P,DeBusk W F.2005.Visible-near infrared reflectance spectroscopy for rapid,nondestructive assessment of wetland soil quality.J Environ Qual.34:1422-1434.
Cozzolino D,Morón A.2006.Potential of near-infrared reflectance spectroscopy and chemometrics to predict soil organic carbon fractions.Soil Tillage Res.85:78-85.
Dunn B W,Batten G D,Beecher H G,Ciavarella S.2002.The potential of near-infrared reflectance spectroscopy for soil analysis-a case study from the Riverine Plain of southeastern Australia.Aust J Exp Agric.42:607-614.
Esbensen K H,Guyot D,Westad F,Houmoller L P.2002.Multivariate Data Analysis in Practice:An Introduction to Multivariate Data Analysis and Experimental Design.CAMOProcess AS,Oslo.
Ge Y F,Morgan C L S,Ackerson J P.2014.VisNIR spectra of dried ground soils predict properties of soils scanned moist and intact.Geoderma.221-222:61-69.
Islam K,Singh B,McBratney A.2003.Simultaneous estimation of several soil properties by ultra-violet,visible,and near-infrared reflectance spectroscopy.Aust J Soil Res.41:1101-1114.
Janik L J,Forrester S T,Rawson A.2009.The prediction of soil chemical and physical properties from mid-infrared spectroscopy and combined partial least-squares regression and neural networks(PLS-NN)analysis.Chemom Intell Lab Syst.97:179-188.
Ji W,Viscarra Rossel R A,Shi Z.2015.Accounting for the effects of water and the environment on proximally sensed vis-NIR soil spectra and their calibrations.Eur J Soil Sci.66:555-565.
Jiang Q H,Chen Y Y,Guo L,Fei T,Qi K.2016.Estimating soil organic carbon of cropland soil at different levels of soil moisture using VIS-NIR spectroscopy.Remote Sens.8:755.
Kruse F A,Lefkoff A B,Boardman J W,Heidebrecht K B,Shapiro A T,Barloon P J,Goetz A F H.1993.The spectral image processing system(SIPS)-interactive visualization and analysis of imaging spectrometer data.Remote Sens Environ.44:145-163.
Liu W D,Baret F,Gu X F,Tong Q X,Zheng L F,Zhang B.2002.Relating soil surface moisture to reflectance.Remote Sens Environ.81:238-246.
Lobell D B,Asner G P.2002.Moisture effects on soil reflectance.Soil Sci Soc Am J.66:722-727.
Minasny B,McBratney A B,Bellon-Maurel V,Roger J M,Gobrecht A,Ferrand L,Joalland S.2011.Removing the effect of soil moisture from NIR diffuse reflectance spectra for the prediction of soil organic carbon.Geoderma.167-168:118-124.
Muller E,Décamps H.2001.Modeling soil moisture-reflectance.Remote Sens Environ.76:173-180.
Nocita M,Stevens A,Noon C,van Wesemael B.2013.Prediction of soil organic carbon for different levels of soil moisture using Vis-NIR spectroscopy.Geoderma.199:37-42.
Pope R M,Fry E S.1997.Absorption spectrum(380-700 nm)of pure water.II.Integrating cavity measurements.Appl Opt.36:8710-8723.
Reeves III J B,Smith D B.2009.The potential of mid-and near-infrared diffuse reflectance spectroscopy for determining major-and trace-element concentrations in soils from a geochemical survey of North America.Appl Geochem.24:1472-1481.
Rienzi E A,Mijatovic B,Mueller T G,Matocha C J,Sikora F J,Castrignan`o A.2014.Prediction of soil organic carbon under varying moisture levels using reflectance spectroscopy.Soil Sci Soc Am J.78:958-967.
Roberts J J,Cozzolino D.2016.Wet or dry?The effect of sample characteristics on the determination of soil properties by near infrared spectroscopy.Trac Trends Anal Chem.83:25-30.
Roger J M,Chauchard F,Bellon-Maurel V.2003.EPO-PLSexternal parameter orthogonalisation of PLS application to temperature-independent measurement of sugar content of intact fruits.Chemom Intell Lab Syst.66:191-204.
Roudier P,Hedley C B,Lobsey C R,Viscarra Rossel R A,Leroux C.2017.Evaluation of two methods to eliminate the effect of water from soil vis-NIR spectra for predictions of organic carbon.Geoderma.296:98-107.
Summers D,Lewis M,Ostendorf B,Chittleborough D.2011.Visible near-infrared reflectance spectroscopy as a predictive indicator of soil properties.Ecol Indic.11:123-131.
Twomey S A,Bohren C F,Mergenthaler J L.1986.Reflectance and albedo differences between wet and dry surfaces.Appl Opt.25:431-437.
Viscarra Rossel R A,Behrens T,Ben-Dor E,Brown D J,Demattê J A M,Shepherd K D,Shi Z,Stenberg B,Stevens A,Adamchuk V,A¨?chi H,Barth`es B G,Bartholomeus HM,Bayer A D,Bernoux M,B?ttcher K,Brodsk′y L,Du CW,Chappell A,Fouad Y,Genot V,Gomez C,Grunwald S,Gubler A,Guerrero C,Hedley C B,Knadel M,Morrás H JM,Nocita M,Ramirez-Lopez L,Roudier P,Campos E MR,Sanborn P,Sellitto V M,Sudduth K A,Rawlins B G,Walter C,Winowiecki L A,Hong S Y,Ji W.2016.A global spectral library to characterize the world’s soil.Earth-Sci Rev.155:198-230.
Viscarra Rossel R A,Walvoort D J J,McBratney A B,Janik LJ,Skjemstad J O.2006.Visible,near infrared,mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties.Geoderma.131:59-75.
Viscarra Rossel R A,Webster R.2012.Predicting soil properties from the Australian soil visible-near infrared spectroscopic database.Eur J Soil Sci.63:848-860.
Volkan Bilgili A,van Es H M,Akbas F,Durak A,Hively WD.2010.Visible-near infrared reflectance spectroscopy for assessment of soil properties in a semi-arid area of Turkey.JArid Environ.74:229-238.
Wijewardane N K,Ge Y F,Morgan C L S.2016.Moisture insensitive prediction of soil properties from VNIR reflectance spectra based on external parameter orthogonalization.Geoderma.267:92-101.
Wold S,Sj?str?m M,Eriksson L.2001.PLS-regression:A basic tool of chemometrics.Chemom Intell Lab Syst.58:109-130.
Wu C Y,Jacobson A R,Laba M,Baveye P C.2009.Alleviating moisture content effects on the visible near-infrared diffuse-reflectance sensing of soils.Soil Sci.174:456-465.
Zhu Y D,Weindorf D C,Chakraborty S,Haggard B,Johnson S,Bakr N.2010.Characterizing surface soil water with field portable diffuse reflectance spectroscopy.J Hydrol.391:133-140.
Zornoza R,Guerrero C,Mataix-Solera J,Scow K M,Arcenegui V,Mataix-Beneyto J.2008.Near infrared spectroscopy for determination of various physical,chemical and biochemical properties in Mediterranean soils.Soil Biol Biochem.40:1923-1930.
Arslan H,Tasan M,Yildirim D,Koksal E S,Cemek B.2014.Predicting field capacity,wilting point,and the other physical properties of soils using hyperspectral reflectance spectroscopy:Two different statistical approaches.Environ Monit Assess.186:5077-5088.
Banin A,Amiel A.1970.A correlative study of the chemical and physical properties of a group of natural soils of Israel.Geoderma.3:185-198.
Ben-Dor E,Banin A.1995.Near-infrared analysis as a rapid method to simultaneously evaluate several soil properties.Soil Sci Soc Am J.59:364-372.
Ben-Dor E,Kindel B,Goetz A F H.2004.Quality assessment of several methods to recover surface reflectance using synthetic imaging spectroscopy data.Remote Sens Environ.90:389-404.
Castaldi F,Chabrillat S,Jones A,Vreys K,Bomans B,van Wesemael B.2018.Soil organic carbon estimation in croplands by hyperspectral remote APEX data using the LUCAS topsoil database.Remote Sens.10:153.
Castaldi F,Palombo A,Pascucci S,Pignatti S,Santini F,Casa R.2015.Reducing the influence of soil moisture on the estimation of clay from hyperspectral data:a case study using simulated PRISMA data.Remote Sens.7:15561-15582.
Chabrillat S,Ben-Dor E,Viscarra Rossel R A,Demattê J A M.2013.Quantitative soil spectroscopy.Appl Environ Soil Sci.2013:616578.
Chabrillat S,Goetz A F H,Krosley L,Olsen H W.2002.Use of hyperspectral images in the identification and mapping of expansive clay soils and the role of spatial resolution.Remote Sens Environ.82:431-445.
Chang C W,Laird D A,Mausbach M J,Hurburgh Jr C R.2001.Near-infrared reflectance spectroscopy-principal components regression analyses of soil properties.Soil Sci Soc Am J.65:480-490.
Christy C D.2008.Real-time measurement of soil attributes using on-the-go near infrared reflectance spectroscopy.Comput Electron Agric.61:10-19.
Clark R N.1999.Spectroscopy of rocks and minerals,and principles of spectroscopy.In Rencz A N(ed.)Manual of Remote Sensing,Vol.3,Remote Sensing for the Earth Sciences.John Wiley and Sons,New York.pp.3-58.
Cohen M J,Prenger J P,DeBusk W F.2005.Visible-near infrared reflectance spectroscopy for rapid,nondestructive assessment of wetland soil quality.J Environ Qual.34:1422-1434.
Cozzolino D,Morón A.2006.Potential of near-infrared reflectance spectroscopy and chemometrics to predict soil organic carbon fractions.Soil Tillage Res.85:78-85.
Dunn B W,Batten G D,Beecher H G,Ciavarella S.2002.The potential of near-infrared reflectance spectroscopy for soil analysis-a case study from the Riverine Plain of southeastern Australia.Aust J Exp Agric.42:607-614.
Esbensen K H,Guyot D,Westad F,Houmoller L P.2002.Multivariate Data Analysis in Practice:An Introduction to Multivariate Data Analysis and Experimental Design.CAMOProcess AS,Oslo.
Ge Y F,Morgan C L S,Ackerson J P.2014.VisNIR spectra of dried ground soils predict properties of soils scanned moist and intact.Geoderma.221-222:61-69.
Islam K,Singh B,McBratney A.2003.Simultaneous estimation of several soil properties by ultra-violet,visible,and near-infrared reflectance spectroscopy.Aust J Soil Res.41:1101-1114.
Janik L J,Forrester S T,Rawson A.2009.The prediction of soil chemical and physical properties from mid-infrared spectroscopy and combined partial least-squares regression and neural networks(PLS-NN)analysis.Chemom Intell Lab Syst.97:179-188.
Ji W,Viscarra Rossel R A,Shi Z.2015.Accounting for the effects of water and the environment on proximally sensed vis-NIR soil spectra and their calibrations.Eur J Soil Sci.66:555-565.
Jiang Q H,Chen Y Y,Guo L,Fei T,Qi K.2016.Estimating soil organic carbon of cropland soil at different levels of soil moisture using VIS-NIR spectroscopy.Remote Sens.8:755.
Kruse F A,Lefkoff A B,Boardman J W,Heidebrecht K B,Shapiro A T,Barloon P J,Goetz A F H.1993.The spectral image processing system(SIPS)-interactive visualization and analysis of imaging spectrometer data.Remote Sens Environ.44:145-163.
Liu W D,Baret F,Gu X F,Tong Q X,Zheng L F,Zhang B.2002.Relating soil surface moisture to reflectance.Remote Sens Environ.81:238-246.
Lobell D B,Asner G P.2002.Moisture effects on soil reflectance.Soil Sci Soc Am J.66:722-727.
Minasny B,McBratney A B,Bellon-Maurel V,Roger J M,Gobrecht A,Ferrand L,Joalland S.2011.Removing the effect of soil moisture from NIR diffuse reflectance spectra for the prediction of soil organic carbon.Geoderma.167-168:118-124.
Muller E,Décamps H.2001.Modeling soil moisture-reflectance.Remote Sens Environ.76:173-180.
Nocita M,Stevens A,Noon C,van Wesemael B.2013.Prediction of soil organic carbon for different levels of soil moisture using Vis-NIR spectroscopy.Geoderma.199:37-42.
Pope R M,Fry E S.1997.Absorption spectrum(380-700 nm)of pure water.II.Integrating cavity measurements.Appl Opt.36:8710-8723.
Reeves III J B,Smith D B.2009.The potential of mid-and near-infrared diffuse reflectance spectroscopy for determining major-and trace-element concentrations in soils from a geochemical survey of North America.Appl Geochem.24:1472-1481.
Rienzi E A,Mijatovic B,Mueller T G,Matocha C J,Sikora F J,Castrignan`o A.2014.Prediction of soil organic carbon under varying moisture levels using reflectance spectroscopy.Soil Sci Soc Am J.78:958-967.
Roberts J J,Cozzolino D.2016.Wet or dry?The effect of sample characteristics on the determination of soil properties by near infrared spectroscopy.Trac Trends Anal Chem.83:25-30.
Roger J M,Chauchard F,Bellon-Maurel V.2003.EPO-PLSexternal parameter orthogonalisation of PLS application to temperature-independent measurement of sugar content of intact fruits.Chemom Intell Lab Syst.66:191-204.
Roudier P,Hedley C B,Lobsey C R,Viscarra Rossel R A,Leroux C.2017.Evaluation of two methods to eliminate the effect of water from soil vis-NIR spectra for predictions of organic carbon.Geoderma.296:98-107.
Summers D,Lewis M,Ostendorf B,Chittleborough D.2011.Visible near-infrared reflectance spectroscopy as a predictive indicator of soil properties.Ecol Indic.11:123-131.
Twomey S A,Bohren C F,Mergenthaler J L.1986.Reflectance and albedo differences between wet and dry surfaces.Appl Opt.25:431-437.
Viscarra Rossel R A,Behrens T,Ben-Dor E,Brown D J,Demattê J A M,Shepherd K D,Shi Z,Stenberg B,Stevens A,Adamchuk V,A¨?chi H,Barth`es B G,Bartholomeus HM,Bayer A D,Bernoux M,B?ttcher K,Brodsk′y L,Du CW,Chappell A,Fouad Y,Genot V,Gomez C,Grunwald S,Gubler A,Guerrero C,Hedley C B,Knadel M,Morrás H JM,Nocita M,Ramirez-Lopez L,Roudier P,Campos E MR,Sanborn P,Sellitto V M,Sudduth K A,Rawlins B G,Walter C,Winowiecki L A,Hong S Y,Ji W.2016.A global spectral library to characterize the world’s soil.Earth-Sci Rev.155:198-230.
Viscarra Rossel R A,Walvoort D J J,McBratney A B,Janik LJ,Skjemstad J O.2006.Visible,near infrared,mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties.Geoderma.131:59-75.
Viscarra Rossel R A,Webster R.2012.Predicting soil properties from the Australian soil visible-near infrared spectroscopic database.Eur J Soil Sci.63:848-860.
Volkan Bilgili A,van Es H M,Akbas F,Durak A,Hively WD.2010.Visible-near infrared reflectance spectroscopy for assessment of soil properties in a semi-arid area of Turkey.JArid Environ.74:229-238.
Wijewardane N K,Ge Y F,Morgan C L S.2016.Moisture insensitive prediction of soil properties from VNIR reflectance spectra based on external parameter orthogonalization.Geoderma.267:92-101.
Wold S,Sj?str?m M,Eriksson L.2001.PLS-regression:A basic tool of chemometrics.Chemom Intell Lab Syst.58:109-130.
Wu C Y,Jacobson A R,Laba M,Baveye P C.2009.Alleviating moisture content effects on the visible near-infrared diffuse-reflectance sensing of soils.Soil Sci.174:456-465.
Zhu Y D,Weindorf D C,Chakraborty S,Haggard B,Johnson S,Bakr N.2010.Characterizing surface soil water with field portable diffuse reflectance spectroscopy.J Hydrol.391:133-140.
Zornoza R,Guerrero C,Mataix-Solera J,Scow K M,Arcenegui V,Mataix-Beneyto J.2008.Near infrared spectroscopy for determination of various physical,chemical and biochemical properties in Mediterranean soils.Soil Biol Biochem.40:1923-1930.