RoSCo: A new tool to navigate Rosetta’s dataset

The Rosetta mission to comet 67P/Churyumov-Gerasimenko (hereafter 67P) provided an unparalleled dataset that has revolutionized our understanding of comets. Rosetta observed activity on 67P for over two years, using its large instrument payload to acquire over 200 GB of data with high spatial and temporal resolution (Taylor et al. 2017). Despite this wealth of data, one of Rosetta’s primary scientific goals — unraveling the mechanisms driving cometary activity — remains unrealized (Vincent et al. 2019, Thomas et al. 2019, Keller and Kührt 2020). The sheer volume and complexity of the data, combined with the lack of efficient tools, have made comprehensive analysis challenging.

Currently, retrieving all data associated with a specific region of interest (ROI) requires manually searching through thousands of images (Barrington et al. 2023) — a daunting and time-consuming task. As a result, while several surface changes have been documented  (Groussin et al. 2015; El-Maarry et al. 2017; Pajola et al. 2017; Vincent et al. 2019; Fornasier et al. 2019a,b; Birch et al. 2019; Jindal et al. 2022; Davidsson et al. 2022; Jindal et al. 2024), many significant and subtle changes remain undetected (e.g., Barrington et al. (2023)), leaving gaps in our understanding of 67P’s evolution. Discovering and characterizing these changes could provide critical insights into the processes driving cometary activity, shedding light on when, where, and how comets erode, all of which remain poorly understood (El-Maarry et al. 2019, Vincent et al. 2019).

With no new missions to comets on the horizon, Rosetta’s dataset will remain the cornerstone of cometary science for at least the next decade, if not longer. To fully realize its potential and enable efficient and comprehensive querying and analysis of all its data, we are creating an open-source tool — the Rosetta Search and Characterization Tool (RoSCo) — that is capable of efficiently and accurately mapping Rosetta data onto 67P’s complex shape. RoSCo allows users to select a ROI on a three-dimensional shape model of 67P and returns all associated data acquired by Rosetta’s Narrow Angle Camera (NAC, Keller et al. 2007). Furthermore, the tool also allows users to analyze the data and map changes on a pixel-scale, which may then be mapped directly onto the shape model of the comet (see Figure 1), allowing subsequent modelling.

These capabilities make RoSCo an all-in-one tool for analyzing Rosetta NAC data that reduces the analysis time from weeks to hours and provides, for the first time, an efficient way for comprehensively mapping the evolution of 67P’s surface. RoSCo utilizes publicly available routines through USGS’s Integrated Software for Imagers and Spectrometers (ISIS) as well as the Navigation and Ancillary Information Facility’s (NAIF) SPICE toolkit (Acton 1996), making it readily adaptable to other Rosetta instruments and upcoming and future small body missions such as Lucy (Levison et al. 2021), Hera (Michel et al. 2022), and Ramses (Kueppers et al. 2023).

Fig. 1. Workflow demonstration for RoSCo. (a/b) Two images taken months apart of an ROI within the Hatmehit region on 67P (red boxes). Differences in orientation and illumination make change detection challenging. Using RoSCo, images are projected into a common reference frame (a_i and b_i), enabling pixel-level comparisons. Users can mark and save observed changes on these projected images (c), which can then be mapped onto the comet’s shape model (d) and saved externally on a facet-by-facet basis. For clarity, (c) shows the net change (2016–2014), with ∼100 additional changes identified in intervening images. “Erosion” indicates smooth terrain loss where new features are exposed or scarps form, while “Deposition” denotes areas where features are muted or buried under fresh smooth terrain layers.

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