From Expert Mapping to Automated Planetary Geomorphometry: The MarsCONE Workflow for Cone Analysis

Planetary geology is based on fundamental terrestrial geological principles combined with modern emerging methodologies. The increasing amount of available high-resolution planetary remote-sensing datasets enable a rapid expansion of the possibilities for quantitative geomorphological analysis, which is fundamental for landforms classification and their further interpretations. However, many landform measurements still rely on expert visual interpretation and manual mapping, limiting reproducibility and scalability. With hundreds of thousands of landforms currently recognized on the planet’s surface, Martian pitted cones provide a clear example of this challenge. Although almost near-global orbital image coverage has enabled their automated identification and provided key insights into their spatial distribution, systematic morphometric analysis remains poorly constrained because manual measurements are highly labour-intensive, depend on spatially limited topographic datasets, and often involve non-standardized methodology protocols.

To address this challenge and enable the development of the global morphometric dataset, MarsCONE, an open-source workflow for automatic morphological analysis of Martian pitted cones, has been developed and publicly released (Śledziowski et al., 2026). It constitutes an important step from expert-based mapping toward reproducible planetary geomorphometry. MarsCONE uses high-resolution digital elevation models (DEMs), including High Resolution Imaging Science Experiment (HiRISE)-derived DEMs, to automate the extraction of pitted cone morphometric parameters. The workflow formalizes an often subjective, expert-defined measurement protocol and the detection of morphological pointsinto a transparent processing chain, including topographic data preparation, transect generation, profile extraction, morphological point detection, cross-transect aggregation, uncertainty handling, and data export.

To constrain and validate the performance of MarsCONE against expert-based manual mapping, we compared the morphometric parameters obtained during eight hours of manual analysis with those automatically calculated by MarsCONE in only a few minutes. This comparison demonstrates the broad potential of automation in planetary geomorphology by reducing repetitive manual work, improves reproducibility, and enabling the standardized and consistent analysis of large landform populations. Importantly, MarsCONE is not intended to replace expert geological interpretation. Instead, it makes expert-informed measurement procedures reusable, scalable, and easier to validate.

The MarsCONE workflow is also relevant to the broad application of machine learning and data-driven methods in planetary exploration. The automatic detection methods depend on reliable and interpretable feature datasets before classification, clustering, or prediction can be meaningfully attempted. MarsCONE contributes to this prerequisite by generating quality-controlled morphometric descriptors, including cone dimensions, height, depression depth, flank geometry, cross-transect variability, and uncertainty-related indicators. These outputs can support downstream applications such as supervised classification, unsupervised clustering, anomaly detection, analogue comparison, and population-scale geomorphological studies.

Nevertheless, the original Python-based MarsCONE tool requires programming knowledge and script modification, which may limit its accessibility to a wider range of users. To make MarsCONE more user-friendly beyond computational experts, we are developing an updated version, MarsCONE 2.0, featuring a graphical user interface that lowers the technical barrier for users applying automated morphometry. The new interface enables parameter configuration, DEM visualization, cross-section inspection, review of automatic detections and subsequent changes of the detection, and export of structured results. Altogether, this improvement makes reproducible computational workflows more accessible to planetary scientists with different levels of programming experience.

Through the updated version of MarsCONE, we also address the geological complexity of pitted cone morphology. The newly added modules and tool capabilities enable the analysis of the overlapping cones with multiple summit craters. This advancement improves the robustness of morphometric analyses in complex volcanic fields and expands the applicability of the tool to more realistic and heterogeneous planetary surfaces.

Altogether, MarsCONE demonstrates that democratizing emerging computational methods in planetary science does not begin only with advanced algorithms. It also requires transparent tools that transform expert interpretation into reproducible, interpretable, and reusable datasets. Automated planetary geomorphometry therefore provides a practical pathway from manual mapping to scalable, data-driven analysis of planetary surfaces.

 

Resources:

Śledziowski, J., Pieterek, B., & Jones, T. J. (2026). MarsCONE: A software toolbox for automatic morphological analysis of Martian pitted-cones. SoftwareX, 102608. https://doi.org/10.1016/j.softx.2026.102608