Comparison of two methods for estimation of soil water content from measured reflectance

Abstract

Comparison of two methods for estimation of soil water content from measured reflectance. Can. J. Soil Sci. 92: 845Á857. Remote sensing (RS) technology has increasingly been used in soil water content estimation, but highly accurate estimates of soil water content are still difficult to obtain using this technique. This study aims to determine the wavelengths at which the reflectance is most sensitive to changes in soil water contents (u). Four types of soils were selected and light reflectance (l) was measured at different u. Results showed that parabolic functions fit u with measured l very well but only for individual wavelengths. Multivariate linear functions of u with measured l at visually selected characteristic wavelengths led to improved predictions, but the coefficients of determination between the soil water content and measured reflectance (R 2 ranged from 0.788 to 0.925 for the four soils) were still not high for the studied soils. Stepwise multiple linear regressions between u and measured l showed higher coefficients of determination (R 2 increased to 0.99 when the number of the statistically selected wavelengths increased) than the multiple regression, but had lower coefficients of determination than the stepwise multiple linear regressions between u and the normalized band depths (D n). The multi-variable linear functions fitted the measured u vs. D n best with much higher R 2 values, even when a single wavelength was used. Re-sampling wavelengths of less than 20 nm preserved the main features of the original reflectance for the studied soils. Parameters were fitted for the quadratic functions using the re-sampled reflectance data at 20-nm wavelength intervals for further estimation of soil water content, which was considered potentially applicable in RS technology for estimating soil water content provided that soils are relatively homogeneous. In conclusion, stepwise multiple linear regression functions between u vs. D n are statistically precise and are recommended for estimating soil water content from reflectance. Parameters for quadratic functions relating soil water content to the observed reflectance could be potentially used in RS technology for estimating soil water content.

Modeling soil cation concentration and sodium adsorption ratio using observed diffuse reflectance spectra

“…4), and there were no abrupt changes of R e in any band range. The observed R e curves of this research were very different from R e of soil moisture (Whiting et al 2004;Li et al 2012), of Fe oxides (Scheinost et al 1998), of soil mineral composition (Viscarra-Rossel and Behrens 2010), and of heavy metals (Wu et al 2007), but similar to the R e curves for soil chemical properties (such as Ca, Mg, Fe, Mn, and K) in the same wavelength bands (Udelhoven et al 2003); however, they obtained R 2 values as high as 0.91 and 0.94 for predictions of Ca and Mg, respectively. It seemed that their spectra pretreatment of minimum minus maximum normalization helped in improving modeling performance.…”

“…The properties of these soil samples showed strong spatial variability with all Cv > 1 (Nielsen and Bouma 1985), decreasing the modeling performance. Model performance was excellent for the artificially configured soils (R 2 >0.99 for the best models relating soil water content to normalized band depth for their four different soils), in which only soil property of water content changed (Li et al 2012).…”

“…Their results indicated that the selected spectral models successfully predicted soil salt content and SOM. Several other studies also focused on using reflectance spectroscopy analysis to predict soil properties (Weng et al 2010;Aldabaa et al 2015;Fan et al 2015), such as electrical conductivity (Moreira et al 2015), pH (Terra et al 2015), and other physicochemical properties (Li et al 2012;Zhang et al 2016).…”

Spectral Analysis and Estimations of Soil Salt and Organic Matter Contents

“…Laboratory spectra of all the soil samples were observed outdoors using an ASD FieldSpec portable spectrometer (Analytical Spectral Devices Inc., Boulder, CO) (Li et al, 2012). The wavelength of the ASD spectrometer ranges between 325 and 1,075 nm, including a sampling interval of 1.5 nm and a constant spectral resolution of 3.5 nm.…”

“…(Abbas et al, 2010;Haskard and Lark, 2009;Hummel et al, 2001;Islam et al, 2005;Li et al, 2012;Melendez-Pastor et al, 2008;Palacios-Orueta and Ustin, 1998;Stoner and Baumgardner, 1981;Summers et al, 2011;Thomasson et al, 2001;Whiting et al, 2004). Dehaan and Talyor (2002) characterized the spatial distributions of irrigation-induced soil salinity using field-derived spectra of saline soils and related vegetation as indicators.…”