EARTHARXIV PREPRINT

CETUS: How Far Do Representations Trained on Earth Transfer to Cassini SAR of Titan?

Cassini synthetic aperture radar (SAR) images reveal the dunes, plains, and lake basins of Titan, providing an instance of representations learned from Earth imagery for planetary terrain classification. Cross-domain Evaluation of Earth-to-Titan Transfer Using SAR (CETUS) compares features from DINOv2, DOFA and CROMA w...

MANTLE: A Framework for Adaptive In-Situ Planetary Perception Using a Modular Uplink Principle

Planetary surface exploration missions rely increasingly on autonomous robotic platforms capable of interpreting complex terrain to ensure safe navigation, enable targeted science, and improve operational efficiency, as demonstrated across past Mars missions from Viking through Perseverance. Among the key perception ca...

MarsRecon: Self-Supervised and Multimodal Surface Representations for Mars

This work presents MarsRecon, a geospatially aware pipeline for learning visual and multimodal representations from HiRISE observations of Olympus Mons, and establishes a working Mars-specific pretraining and retrieval pipeline.

Revisiting the Task of Building Damage Assessment by Satellite Imaging

Natural disasters such as earthquakes, tropical storms, and floods cause extensive damage to buildings, and rapid, reliable damage maps are essential to guide emergency response. Automating this task, referred to as building damage assessment (BDA), from satellite imagery, has become an active research topic at the int...

Automatic Crater Classification Using a Deep‐Learning‐Based Pipeline

Identifying and classifying impact craters on Mars is crucial for understanding the planet's geological history and surface evolution. Traditional crater classification relies on manual annotation methods, which are often limited by human biases and the difficulty of interpreting geomorphological features. Classifyin...

Deep learning-based landslide detection using Sentinel-1 SAR imagery in the Chilean Patagonia