Modeling soil moisture-reflectance

Spectral information on soil is not easily available as vegetation and farm works prevent direct observation of soil responses. However, then is an in creasing need to include soil reflectance values in spectral unmixing algor ithms or in classification approaches. Zn most cases, the impact of soil mo isture on the reflectance is unknown and therefore ignored. The objective o f this study was to model reflectance changes due to soil moisture in a rea l field situation using multiresolution airborne Spot data. As the direct o bservation of soils is only possible in the absence of vegetation, the effe ctive remote sensing of soil moisture is limited to a few days each year. I II such a favorable time window, modeling the soil moisture-reflectance rel ationships was found possible. The proposed exponential model was not valid when all soil categories were considered together. However, when fitted to each category, the RMS error on moisture estimates ranged from 2.0% to 3.5 % except for silty soils with crusting problems (6%). Results also indicate d that, when the soils have similar colors (i.e. same hue), soil categories can be partly grouped and the model can be simplified, using the same inte rcept coefficients. This study has potential application for;he definition of a more generalized model of the soil reflectance. It shows that the impa ct of soil moisture on reflectance could be higher than differences in refl ectance due to the soil categories. (C) 2001 Elsevier Science Inc. All righ ts reserved.