  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, etc...), the transfer of light in surface and atmospheric
medium are highly non-linear. The exact simulation of non-linearities can be
estimated at very high numerical cost. Here I propose a very simple non-linear
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 are not expected to follow the
same trend.
