Visible near-infrared reflectance spectroscopy as a predictive indicator of soil properties

Abstract It is becoming increasingly important to improve spatial resolutions of soil maps as a fundamental information layer for studying ecological processes and to tackle land degradation. There is growing interest in the use of remote sensing technologies to assist the identification and delineation of spatial variation in soils. This paper investigates whether selected properties of extensively weathered, low fertility soils can be predicted using high-resolution reflectance spectra over the range 400–2500 nm. Clay content, carbonate concentration, organic carbon content and iron oxide content were analysed for 300 soil samples collected from the Jamestown, Belalie district, South Australia. The paper also examines the efficacy of this soil analysis methodology to supplement or replace traditional soil sampling in soil survey to increase sampling density and improve the spatial resolution of soil maps. Reflectance spectra were obtained from air-dried samples under controlled laboratory conditions using an ASD FieldSpec Pro spectroradiometer. Partial least squares regression was used to examine relationships between soil mineralogy, clay content and organic carbon and the reflectance spectra and identify the wavelengths contributing to prediction of these soil properties. Results show that it is possible to predict clay content, soil organic carbon, iron oxide content and carbonate content. Cross-validation R2 values for all analyses were above 0.5 and the residual prediction difference (RPD) was acceptable for all soil properties. Carbonate and clay content were more accurately predicted than iron oxide and organic carbon. All samples were collected from the same geographical area such that they represented physical properties over a naturally occurring range and provide a prediction that could be related to subsequent image analysis or be used to carry out local scale soil survey. A rapid and reliable form of soil mapping could be developed from this methodology.

[1]  Budiman Minasny,et al.  From pedotransfer functions to soil inference systems , 2002 .

[2]  J. Walker,et al.  Australian Soil and Land Survey Field Handbook , 1984 .

[3]  C. Hurburgh,et al.  Near-Infrared Reflectance Spectroscopy–Principal Components Regression Analyses of Soil Properties , 2001 .

[4]  R. Tiner,et al.  Remotely-sensed indicators for monitoring the general condition of "natural habitat" in watersheds: an application for Delaware's Nanticoke River watershed , 2004 .

[5]  E. Ben-Dor,et al.  NEAR INFRARED ANALYSIS (NIRA) AS A METHOD TO SIMULTANEOUSLY EVALUATE SPECTRAL FEATURELESS CONSTITUENTS IN SOILS , 1995 .

[6]  A. Klute Methods of soil analysis. Part 1. Physical and mineralogical methods. , 1988 .

[7]  H. Beecher,et al.  The potential of near-infrared reflectance spectroscopy for soil analysis — a case study from the Riverine Plain of south-eastern Australia , 2002 .

[8]  F. D. van der Meer,et al.  Spectral reflectance of carbonate mineral mixtures and bidirectional reflectance theory: Quantitative analysis techniques for application in remote sensing , 1995 .

[9]  E. Ben-Dor The reflectance spectra of organic matter in the visible near-infrared and short wave infrared region (400-2500 nm) during a controlled decomposition process , 1997 .

[10]  Andrew Rawson,et al.  Rapid Prediction of Soil Water Retention using Mid Infrared Spectroscopy , 2007 .

[11]  L. Janik,et al.  Can mid infrared diffuse reflectance analysis replace soil extractions , 1998 .

[12]  A. Karnieli,et al.  Mapping of several soil properties using DAIS-7915 hyperspectral scanner data - a case study over clayey soils in Israel , 2002 .

[13]  T. Cudahy,et al.  Deriving quantitative dust measurements related to iron ore handling from airborne hyperspectral data , 2003 .

[14]  H. Abdi Partial Least Squares (PLS) Regression. , 2003 .

[15]  Alex B. McBratney,et al.  Diffuse reflectance spectrometry as a proximal sensing tool for precision agriculture , 2001 .

[16]  Marvin H. Hall,et al.  Carbon and Nitrogen Analysis of Soil Fractions Using Near-Infrared Reflectance Spectroscopy , 1991 .

[17]  G. Gee,et al.  Particle-size Analysis , 2018, SSSA Book Series.

[18]  Eyal Ben-Dor,et al.  Quantitative mapping of the soil rubification process on sand dunes using an airborne hyperspectral sensor , 2006 .

[19]  H. Condit THE SPECTRAL REFLECTANCE OF AMERICAN SOILS , 1970 .

[20]  E. R. Stoner,et al.  Characteristic variations in reflectance of surface soils , 1981 .

[21]  E. Ben-Dor,et al.  Near-Infrared Reflectance Analysis of Carbonate Concentration in Soils , 1990 .

[22]  K. D. Clarke Landscape scale measurement and monitoring of biodiversity in the Australian rangelands , 2008 .

[23]  D. W. Nelson,et al.  Total Carbon, Organic Carbon, and Organic Matter , 1983, SSSA Book Series.

[24]  R. V. Rossel,et al.  Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties , 2006 .

[25]  Wolfhard Wegscheider,et al.  Spectrophotometric multicomponent analysis applied to trace metal determinations , 1985 .

[26]  L. Janik,et al.  Characterization and analysis of soils using mid-infrared partial least-squares .2. Correlations with some laboratory data , 1995 .

[27]  J. Hummel,et al.  Reflectance technique for predicting soil organic matter. , 1980 .

[28]  Megan Lewis,et al.  Discrimination of arid vegetation composition with high resolution CASI imagery , 2000 .

[29]  L. S. Galvão,et al.  Role of organic matter in obliterating the effects of iron on spectral reflectance and colour of Brazilian tropical soils , 1998 .

[30]  E. Ben-Dor Quantitative remote sensing of soil properties , 2002 .

[31]  R. Henry,et al.  Simultaneous Determination of Moisture, Organic Carbon, and Total Nitrogen by Near Infrared Reflectance Spectrophotometry , 1986 .

[32]  N. Tripathi,et al.  Analysis of VNIR (400–1100 nm) spectral signatures for estimation of soil organic matter in tropical soils of Thailand , 2004 .

[33]  Eyal Ben-Dor,et al.  Near-Infrared Analysis as a Rapid Method to Simultaneously Evaluate Several Soil Properties , 1995 .

[34]  Bertram Ostendorf,et al.  A high resolution broad scale spatial indicator of grain growing profitability for natural resource planning , 2011 .

[35]  G. McCarty,et al.  Mid-Infrared and Near-Infrared Diffuse Reflectance Spectroscopy for Soil Carbon Measurement , 2002 .

[36]  D. Kroetsch,et al.  Particle Size Distribution , 2007 .

[37]  K. Shepherd,et al.  Global soil characterization with VNIR diffuse reflectance spectroscopy , 2006 .

[38]  D. Cozzolino,et al.  The potential of near-infrared reflectance spectroscopy to analyse soil chemical and physical characteristics , 2003, The Journal of Agricultural Science.

[39]  M. Clayton,et al.  OLD-GROWTH NORTHERN HARDWOOD FORESTS: SPATIAL AUTOCORRELATION AND PATTERNS OF UNDERSTORY VEGETATION , 2002 .

[40]  Thomas Blaschke,et al.  Spatial indicators for nature conservation from European to local scale , 2005 .

[41]  Daniel C. Coster,et al.  High dimensional reflectance analysis of soil organic matter , 1992 .

[42]  Nitin K. Tripathi,et al.  Artificial neural network analysis of laboratory and in situ spectra for the estimation of macronutrients in soils of Lop Buri (Thailand) , 2003 .

[43]  R. Isbell Australian Soil Classification , 1996 .

[44]  M. Turmel,et al.  Extractable Al, Fe, Mn, and Si , 2007 .

[45]  C. Elvidge Visible and near infrared reflectance characteristics of dry plant materials , 1990 .

[46]  E. R. Stoner,et al.  REFLECTANCE PROPERTIES OF SOILS , 1986 .

[47]  Alex B. McBratney,et al.  Simultaneous estimation of several soil properties by ultra-violet, visible, and near-infrared reflectance spectroscopy , 2003 .

[48]  Rainer Duttmann,et al.  Prediction of soil property distribution in paddy soil landscapes using terrain data and satellite information as indicators , 2008 .

[49]  P. Williams,et al.  Near-Infrared Technology in the Agricultural and Food Industries , 1987 .