|Lee, Kyou - SUNGKYUNKWAN UNIV/S KOREA|
|Lee, Dong - SUNGKYUNKWAN UNIV/S KOREA|
|Chung, Sun - CHUNGNAM NAT UNIV/S KOREA|
Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 26, 2009
Publication Date: June 21, 2009
Citation: Lee, K.S., Lee, D.H., Sudduth, K.A., Chung, S.O., Kitchen, N.R., Drummond, S.T. 2009. Wavelength Identification and Diffuse Reflectance Estimation for Surface and Profile Soil Properties. Transactions of the ASABE. 52(3):683-695. Interpretive Summary: Measuring the variation in soil properties within fields is an important component of precision agriculture. For many soil properties, it is difficult to obtain enough data to accurately characterize their spatial variation, due to the cost of traditional sampling and laboratory analysis. Sensors that can estimate soil properties without the need for sampling are a promising alternative. One technology that has received considerable attention in this regard is optical reflectance sensing in the visible and near infrared (NIR) wavelength bands. A number of researchers have investigated this approach, but have generally limited their analysis to surface soils. In this study, we examined the use of visible-NIR reflectance sensing to estimate a number of soil properties, both for surface soils and for soils obtained to a depth of about 4 feet in the soil profile. We collected multiple soil samples from ten fields in five Midwestern states and measured their reflectance characteristics in the laboratory. We used statistical techniques to relate the reflectance to laboratory-measured soil properties. We found that visible-NIR reflectance gave good estimates of soil clay, calcium, cation exchange capacity, and organic carbon. We also investigated what wavelengths were most important in the relationship, finding several wavelengths that were important contributors for multiple soil properties. This is an important finding because the need to sense only a few wavelengths could result in a more rugged, inexpensive, and reliable sensor than if the full spectrum was required. The results of this study will provide information that instrumentation engineers and researchers can use to develop new in-field soil sensing technology.
Technical Abstract: Optical diffuse reflectance spectroscopy (DRS) has been used to estimate soil physical and chemical properties, but much of the previous work has been limited to surface soils or to samples obtained from a restricted geographic area. Our objectives in this research were (1) to assess the accuracy of DRS for estimating variation in several important surface and profile soil properties across a wide range of soils from the U.S. Corn Belt, and (2) to determine the wavelength ranges and/or specific wavelengths that should be included in a DRS soil property sensor. Soil cores were obtained to a 120-cm depth from ten fields, two each in Missouri, Illinois, Michigan, South Dakota, and Iowa. Cores were segmented by pedogenic horizon and samples (n=165 for the surface soil horizon, n = 697 for all soil horizons) were analyzed for texture fractions, cations (Ca, Mg, and K) and cation exchange capacity (CEC), pH, total and organic C, and total N using standard laboratory procedures. Spectra were obtained on sieved, air-dried soils from 350 to 2500 nm using a commercial three-detector spectrometer. Reflectance data were related to soil properties using partial least squares (PLS) regression and stepwise multiple linear regression (SMLR). Calibration accuracies varied among the different soil properties, but for a given soil property, similar accuracies were generally obtained with PLS and SMLR. The most accurate estimates, with R2 values above 0.8, were obtained for organic C, clay, CEC, and Ca. When data from each of the three spectrometer detector ranges were analyzed separately with PLS, the third detector range (1770 to 2500 nm) provided results similar to those obtained using the complete spectral range. Discrete wavelength models that described 90% or more of the variance described by a full model were obtained using 8 or fewer wavelengths for the profile dataset and 6 or fewer wavelengths for the surface dataset. Several wavelengths and wavelength ranges common to models for multiple soil properties were identified: 2070 nm, 1870 to 1915 nm, and 2220 to 2410 nm. Thus, these would be important to include in the design of a multiple-wavelength soil property sensor.