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Surface particulate media such as soil and snow have significant impacts on global systems because of their contributions to the radiation balance of the Earth system, their roles in the hydrologic cycle, and their extensive spatial distributions. At regional and global scales, characteristics of soils and snow cover can best be mapped and analyzed using satellite‐based sensors that acquire both spectral and angular reflectance information. Advances in surface reflectance models over the past decade now provide improved interpretation of remote sensing imagery over snow. However, advances have been slower in remote sensing of soil properties and a number of key issues remain. This article begins with an overview of the similarities and differences between particulate media modeling approaches for soil and snow. We review common modeling methods: radiative transfer approximations, numerical solutions, and geometrical optics. Model inversion and validation experiments are summarized and research priorities are discussed.
Nolin et al. (Fri,) studied this question.