InCorr: Interactive Data-Driven Correlation Panels for Digital Outcrop Analysis

InCorr: Interactive Data-Driven Correlation Panels for Digital Outcrop Analysis teaser image

Geological analysis of 3D Digital Outcrop Models (DOMs) for reconstruction of ancient habitable environments is a key aspect of the upcoming ESA ExoMars 2022 Rosalind Franklin Rover and the NASA 2020 Rover Perseverance missions in seeking signs of past life on Mars. Geologists measure and interpret 3D DOMs, create sedimentary logs and combine them in ‘correlation panels’ to map the extents of key geological horizons, and build a stratigraphic model to understand their position in the ancient landscape. Currently, the creation of correlation panels is completely manual and therefore time-consuming, and inflexible. With InCorr we present a visualization solution that encompasses a 3D logging tool and an interactive data-driven correlation panel that evolves with the stratigraphic analysis. For the creation of InCorr we closely cooperated with leading planetary geologists in the form of a design study. We verify our results by recreating an existing correlation analysis with InCorr and validate our correlation panel against a manually created illustration. Further, we conducted a user-study with a wider circle of geologists. Our evaluation shows that InCorr efficiently supports the domain experts in tackling their research questions and that it has the potential to significantly impact how geologists work with digital outcrop representations in general.

Resources

Citation

Thomas Ortner, Andreas Walch, Rebecca Nowak, Robert Barnes, Thomas Höllt, and Meister Eduard Gröller. InCorr: Interactive Data-Driven Correlation Panels for Digital Outcrop Analysis. IEEE Transactions on Visualization and Computer Graphics (Proceedings of IEEE VAST 2020), 27(1): 2021.

BibTeX

@article{ bib:2020_vis_incorr,
author = {Thomas Ortner and Andreas Walch and Rebecca Nowak and Robert Barnes and Thomas H{\"o}llt and Meister Eduard Gr{\"o}ller},
title = { InCorr: Interactive Data-Driven Correlation Panels for Digital Outcrop Analysis },
journal = { IEEE Transactions on Visualization and Computer Graphics (Proceedings of IEEE VAST 2020) },
number = { 1 },
year = { 2021 },
doi = { 10.1109/TVCG.2020.3030409 },
}