MarsCONE: A software toolbox for automatic morphological analysis of Martian pitted-cones

Advances in automated image classification, together with near-global imaging coverage of the Martian surface, have enabled detailed characterization of the spatial distribution of pitted cones, providing a foundation for systematic investigations of their morphological diversity. Concurrently, the continued acquisition of high-resolution Martian imagery over the past decades has allowed photogrammetrically derived digital elevation models (DEMs) to enhance the accessibility, precision, and overall robustness of morphological analyses. However, the number of identified Martian pitted cones causes systematic, manual morphological measurements to be highly labour-intensive and, consequently, impractical for large datasets. To address this challenge, we present a command-line open-source MarsCONE software toolbox, designed to perform automatic cone-morphology detection, and to compute the morphological parameters of Martian pitted cones using High Resolution Imaging Science Experiment (HiRISE)-derived DEMs. The toolbox is built on as a suite of Python tools and Jupyter notebooks, and performs key processing steps including data preparation and transect generation according to user-defined configurations (Generator), signal extraction and landform-point morphology detection (Finder), and cross-transect aggregation with uncertainty handling and data export (Analyzer). This enables MarsCONE to analyze hundreds of pitted cones in a single batch, providing fully reproducible and systematic results within seconds and at minimal computational cost. Consequently, the MarsCONE toolbox improves reproducibility, reduces manual workload, and facilitates large-scale comparative studies of pitted cones across Mars, thereby supporting a more robust understanding of the geological processes governing their formation.