Title: WAVELENGTH IDENTIFICATION FOR REFLECTANCE ESTIMATION OF SURFACE AND SUBSURFACE SOIL PROPERTIES Authors
|Lee, K - SUNGKYUNKWAN UNI S. KOREA|
|Lee, D - SUNGKYUNKWAN UNI S. KOREA|
|Chung, S - CHUNGNAM NAT UNI S. KOREA|
Submitted to: ASABE Annual International Meeting
Publication Type: Proceedings
Publication Acceptance Date: May 10, 2007
Publication Date: June 18, 2007
Repository URL: http://asae.frymulti.com/request.asp?search=1&JID=5&AID=22894&CID=min2007&v=&i=&T=2
Citation: Lee, K.S., Lee, D.H., Sudduth, K.A., Chung, S.O., Drummond, S.T. 2007. Wavelength identification for reflectance estimation of surface and subsurface soil properties. ASABE Annual International Meeting Technical Papers. ASABE, St. Joseph, MI. Paper No. 071046. Available: http://asae.frymulti.com/request.asp?search=1&JID=5&AID=22894&CID=min2007&v=&i=&T=2. 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 in both surface and subsurface soils. 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 surface soil clay, calcium, cation exchange capacity, and organic carbon. When including soils from all depths, results were not quite as good, but were still acceptable. 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 sensing is a potential approach for rapid and reliable on-site estimation of soil properties. In this study, reflectance sensing in visible (VIS) and near-infrared (NIR) wavelengths was combined with partial least squares (PLS) regression to estimate surface and subsurface soil properties, and wavelength bands important for estimating soil properties were identified. Soil cores (120 cm deep) from ten fields in five states in the US cornbelt were segmented by horizon and analyzed in laboratory for texture (sand, silt, and clay fractions), cation exchange capacity (CEC), Ca, Mg, K, pH, total and organic C, and total N. Using air-dried, sieved soil samples, reflectance data were obtained from 350 to 2500 nm with a laboratory spectrometer. Over all soil horizons, cross-validated predictions of organic C were good (R2=0.87, RPD (the ratio of standard deviation to standard error of prediction) =2.78), while predictions of clay fraction, CEC, and pH were also acceptable (0.63 less than R2 less than 0.79, RPD about 2). Calibrations restricted to the surface horizon were somewhat better, with R2 values from 0.81 to 0.85 and RPD values from 2.08 to 2.73 for clay fraction, Ca, CEC, and organic C. Important wavelengths were 380-550 nm and 1700-1850 nm for clay; 430-460, 905, and 1820-1840 nm for CEC; and 390-400, 905, 1340-1360, 1710-1720, and 1840-1880 nm for organic C. These results will be useful in the design and application of in-situ close range sensors for soil physical and chemical properties.