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Depending on the topography and soil characteristics of an area, soil moisture, an important factor in cropproductivity, can be quite variable over the land surface. Thus, a method for determination of soil moisture without thenecessity for exhaustive manual measurements would be beneficial for characterizing soil moisture within a given region orfield. In this study, soil surface reflectance data in the visible and near-infrared regions were analyzed in conjunction withsurface moisture data in a field environment to determine the nature of the relationship between the two, and to identifypotential methods for estimation of soil moisture from remotely sensed data in these wavelengths. Results indicate that it isfeasible to estimate surface (0 to 7.6 cm) soil moisture from visible and near-infrared reflectance, although estimatingmoisture regimes rather than precise water content is perhaps more likely. Furthermore, an exponential model wasappropriate to describe soil moisture from spectral reflectance data. In particular, the visible region of the electromagneticspectrum works well with such a model. A partial least squares analysis with improved R2 values over the single-band modelsindicated that mulitspectral data may add more useful information about soil moisture as compared to single-band data. Theresults also suggested that the performance of reflectance models for moisture estimation is a function of soil types; theestimation results were better for the lighter of the two soils in this study.
Kaleita et al. (Sat,) studied this question.