Recovery of surface reflectance spectra and evaluation of the optical depth of aerosols in the near-IR using a Monte-Carlo approach: Application to the OMEGA observations of high latitude regions of Mars
Mathieu Vincendon, Yves Langevin, Fran\c{c}ois Poulet, Jean-Pierre, Bibring, Brigitte Gondet

TL;DR
This paper introduces a Monte Carlo radiative transfer model to analyze and remove aerosol effects from near-IR spectra of Mars, enabling accurate surface reflectance retrieval and aerosol optical depth estimation from OMEGA data.
Contribution
The study develops a novel Monte Carlo-based method for quantifying atmospheric dust contribution in Martian surface spectra and validating surface reflectance independent of aerosol effects.
Findings
Optical depth of Martian aerosols varies significantly during summer.
Surface ice reflectance can be accurately recovered after aerosol correction.
Dust contamination influences the apparent brightness of ice patches.
Abstract
We present a model of radiative transfer through atmospheric particles based on Monte Carlo methods. This model can be used to analyze and remove the contribution of aerosols in remote sensing observations. We have developed a method to quantify the contribution of atmospheric dust in near-IR spectra of the Martian surface obtained by the OMEGA imaging spectrometer on board Mars Express. Using observations in the nadir pointing mode with significant differences in solar incidence angles, we can infer the optical depth of atmospheric dust, and we can retrieve the surface reflectance spectra free of aerosol contribution. Martian airborne dust properties are discussed and constrained from previous studies and OMEGA data. We have tested our method on a region at 90{\deg}E and 77{\deg}N extensively covered by OMEGA, where significant variations of the albedo of ice patches in the visible…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
