Monte Carlo Radiative Transfer Model for Airless Planetary Surfaces

<p>The poster presents the development of a Monte Carlo Radiative Transfer (MCRT) model to simulate the bidirectional reflectance distribution function (BRDF) of airless planetary surfaces. The study applies both direct and indirect photon path-tracing approaches to analyse light–regolith interactions and validate the simulation against established models (Ciarniello et al., 2014). The model incorporates key surface parameters such as single-scattering albedo, filling factor, and regolith particle properties, with ongoing work to include anisotropic scattering through the Henyey–Greenstein phase function. The results aim to enhance the understanding of reflectance behaviour on airless bodies, such as the Moon and Ceres, and improve radiative-transfer modelling accuracy for planetary remote sensing applications.</p>

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-01
DOI
https://doi.org/10.5281/zenodo.17592370
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00
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article

Monte Carlo Radiative Transfer Model for Airless Planetary Surfaces

Zenodo (CERN European Organization for Nuclear Research)
Atmospheric aerosols and clouds
article

Monte Carlo Radiative Transfer Model for Airless Planetary Surfaces

article en

Abstract

<p>The poster presents the development of a Monte Carlo Radiative Transfer (MCRT) model to simulate the bidirectional reflectance distribution function (BRDF) of airless planetary surfaces. The study applies both direct and indirect photon path-tracing approaches to analyse light–regolith interactions and validate the simulation against established models (Ciarniello et al., 2014). The model incorporates key surface parameters such as single-scattering albedo, filling factor, and regolith particle properties, with ongoing work to include anisotropic scattering through the Henyey–Greenstein phase function. The results aim to enhance the understanding of reflectance behaviour on airless bodies, such as the Moon and Ceres, and improve radiative-transfer modelling accuracy for planetary remote sensing applications.</p>

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 44%
Atmospheric aerosols and clouds
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