Approximation of radiative transfer for surface spectral features

TL;DR

This paper introduces a simple non-linear radiative transfer model that approximates surface spectral features, capturing grain size, mixture effects, and Martian aerosols with low computational cost.

Contribution

A novel analytical non-linear radiative transfer form that improves approximation of surface spectral features over traditional linear models.

Findings

Accurately models grain size and mixture effects on surface spectra.

Effectively approximates Martian mineral aerosol impacts.

Limited applicability to complex Earth aerosols.

Abstract

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.