LAUSR

Remote sensing hyperspectral and, more generally, spectral instruments are common tools to decipher surface features in Earth and Planetary science. While linear mixture is the most common approximation for compounds detection (mineral, water, ice, and so on), the transfer of light in surface and atmospheric medium are highly nonlinear. The exact simulation of nonlinearities can be estimated at very high numerical cost. Here, I propose a very simple nonlinear form (that includes the regular linear area mixture) of radiative transfer to approximate surface spectral feature. I demonstrate that this analytical form is able to approximate the grain size and intimate mixture dependence of surface features. In addition, the same analytical form can approximate the effect of Martian mineral aerosols. Unfortunately, Earth aerosols are more complex (water droplet, water ice, soot, and so on) and are not expected to follow the same trend.