Antoine Lucas

Institut de Physique du Globe de Paris
Planetary and Space Sciences group
External envelopes geochemistry group

CNRS research scientist

About me

My research focuses on surface and near-surface processes such as landslides, avalanches, debris flows, dunes, rivers, lakes, and sediment transport. I use planetary bodies as natural laboratories: Mars, Titan, Venus, the Moon, and icy satellites allow us to test how gravity, atmosphere, climate, volatiles, and surface materials control landscape dynamics beyond the conditions found on Earth.

To address these questions, I combine planetary mission data, remote sensing, image processing, numerical modeling, geophysics, and machine learning. My work sits at the crossroads of geomorphology, planetary science, and natural hazards, with a particular focus on mass wasting, aeolian transport, hydrology, and hydro-gravitational risks.

A geomorphologist by objects of study, a geophysicist by methods, and a planetary scientist by perspective, I define myself as a space hacker, an astro-geologist, a landscape analyst, and a space avalancher.

I am an appointed member of the EuroSAR Science Team for ESA’s EnVision mission to Venus, contributing to the preparation of radar-based investigations of planetary surfaces and their geological evolution.

I also serve on the board of directors of the Planetary Research Cooperative, which supports open and community-led publishing in planetary science, including the diamond open-access journal Planetary Research.

I am the Principal Investigator of the PHYGRAV Platform, which develops physics-based models, surrogate tools, and decision-ready products for landslides, avalanches, tsunamis, and hydro-sedimentary hazards.

Since 2023, I have also been in charge of the Natural Hazards Master’s program at IPGP / Université Paris Cité.

Recent Publications

Bayesian inversion of the Hapke model on (4) Vesta’s avalanches and ejecta: Photometric constraints on regolith evolution

D.T. Nguyen, A. Roque-Bernard, A. Lucas, S. Jacquemoud, and C. Ferrari

A&A, 2026.

abstract PDF url

The Dawn mission revealed significant photometric variability on (4) Vesta, particularly in areas with craters, avalanches, cliffs and ejecta. Understanding how surface processes control these variations is essential to understanding regolith evolution on airless bodies. We test the hypothesis that the photometric behavior of bright units can be explained by granular segregation during mass wasting and impact emplacement rather than by subsequent optical maturation. Using a Bayesian approach, we invert a four-parameter Hapke model at two sites: bright avalanches in Cornelia crater and a fresh ejecta deposit on the Matronalia Rupes scarp. For each geomorphological unit, we adjust median reflectance factors for phase angles ranging from 10∘to 70∘. Because the available data do not identify the opposition effect robustly, the main inversion is complemented by sensitivity tests using literature-based fixed SHOE prescriptions, reported explicitly for Cornelia. We retrieve the Hapke parameters {ω,θ,b,c} with full posteriors. Fresh, bright deposits at both sites exhibit higher single-scattering albedo (ω) than adjacent older or fine-depleted surfaces. Cornelia avalanches also favor higher photometric roughness (θ) than the crater floor and opposite wall. At Cornelia, sensitivity tests show that ω, \barθ, and the relative ordering of terrains remain stable, whereas the absolute values of the phase-function parameters (b,c) depend more strongly on how SHOE is represented. Granular segregation during emplacement explains the brightest units, while optical maturation and surface stabilization explain the darker ones. Even without direct opposition coverage, the baseline inversion and Cornelia SHOE sensitivity tests yield a consistent relative “freshness ranking” that complements morphological superposition. This ranking provides a transferable framework for interpreting regolith processes on airless bodies.
Landslide-Tsurrogate v1.0: A computationally efficient framework for probabilistic tsunami hazard assessment applied to Mayotte (France)

Clea Lumina Denamiel, Alexis Marboeuf, Anne Mangeney, Anne Le Friant, Marc Peruzzetto, Antoine Lucas, Manuel J. Castro Díaz, and Enrique Fernández-Nieto

Geoscientific Model Development, 2026.

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Landslide-Tsurrogate v1.0 is an open-source Python and MATLAB tool that helps scientists quickly estimate the tsunami hazards generated by submarine landslides. Instead of running thousands of heavy deterministic numerical simulations, the software builds surrogate models that reproduce the main results with a fraction of the computational cost. The method relies on a mathematical approach called generalized polynomial chaos expansion, which efficiently explores how uncertain landslide parameters affect tsunami generation. Users can perform sensitivity analyses, identify the most influential parameters, and quantify the variability of possible outcomes. The tool includes a Jupyter Notebook User Manual and interactive MATLAB and Jupyter Notebook interfaces, making it easy to understand the methodology, set up the surrogate simulations and visualize the results. The Landslide-Tsurrogate v1.0 model’s performance is demonstrated through a real-world test case involving five zones in Mayotte (France). For this application, the surrogate models achieve convergence with only 135 deterministic simulations per zone and produce probabilistic results in less than 2 seconds within the user-friendly interfaces used on a basic laptop, demonstrating the computational efficiency of the approach. Beyond this example, the framework can be applied to any coastal region prone to submarine landslides. By combining physical modeling, statistical analysis, and user-friendly design, Landslide-Tsurrogate v1.0 enables faster and more transparent probabilistic tsunami hazard assessments.
Investigating the Detectability of Body Wave Phases from Tidal Ice Cracking Events on Titan with the DragonFly Short-Period Seismometer

L. Delaroque, T. Kawamura, A. Lucas, S. Rodriguez, K. Onodera, H. Shiraishi, R. Yamada, S. Tanaka, M. P. Panning, and R. D. Lorenz

JGR-Planets, 2026.

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Detecting seismic activity on Saturn’s icy moon Titan during the \textitDragonfly mission could provide crucial information on its internal structure. The geological complexity of the moon’s surface suggests significant cyclic tidal deformation, likely leading to the fracturing of the ice shell. Considering realistic source locations and fault geometries, we assess whether a vertical short-period seismometer can detect body waves from a M_w 4.0 icequake. Signal-to-noise ratios are evaluated by comparing the high-frequency content with the expected background noise and instrument capabilities for several ice attenuation scenarios and 1D interior models. Our results indicate that the high-frequency content (\geq1Hz) of M_w ≤4.0 tidal-induced icequakes is likely undetectable under the most unfavorable attenuation scenarios and atmospheric conditions. However, seismic signals in the 0.5-1 Hz band—where P wave reflections dominate—may still be observable for events occurring in potential seismically active regions at ∼800 – 1,000 km from the \textitDragonfly’s landing site. These signals could provide constraints on the thickness of Titan’s outer ice shell, provided that intrinsic attenuation is low and environmental conditions are favorable.