Recent updates on the Multi-Purpose Advanced Tool for Instruments for the Solar System Exploration (MATISSE)

Recent updates on the Multi-Purpose Advanced Tool for Instruments for the Solar System Exploration. G. Nodjoumi1,2,3 V. Camplone1,2, E. Rognini1, M. Giardino1,4, A. Zinzi1,4 - 1Space Science Data Center, Agenzia Spaziale Italiana (ASI), Via del Politecnico snc, 00133, Rome, Italy, 2INAF/Osservatorio Astronomico di Roma (INAF-OAR), Via Frascati 33, 00078, Monte Porzio Catone (RM), Italy, 3School of Science, Constructor University Bremen gGmbH, Bremen, DE, 4Agenzia Spaziale Italiana (ASI), Via del Politecnico snc, 00133, Rome, Italy, Introduction: The Multi-purpose Advanced Tool for the Instruments of the Solar System Exploration (MATISSE): MATISSE [1], is a cutting-edge webbased tool for planetary science analysis, developed and hosted by the Space Science Data Center (SSDC) of the Italian Space Agency (ASI). This tool integrates and visualizes complex datasets from various planetary missions, enabling researchers to perform sophisticated spatial and spectral analyses. Built on a GIS database, the tool allows simultaneous use of multiple data types, displaying planetary data in 2D and 3D via web browsers and REST-based scripting interfaces. MATISSE returns query results as Flexible Image Transport System (FITS) files, which can be conveniently downloaded for further processing and detailed analysis using external tools. Additionally, the MATISSE service is fully accessible via a REST API, facilitating programmatic data retrieval and automation of complex data queries. SSDC’s centralized storage of the majority of MATISSE’s datasets allows for rapid and efficient data access and retrieval, thereby resulting in significantly enhanced user experience and increased productivity. Currently, the functionality of the MATISSE system encompasses support for diverse planetary datasets, including those obtained from Mars, Mercury, Ceres, Didymos, Vesta, and Venus, and the system seamlessly integrates data from notable space missions like NASA’s Mars Reconnaissance Orbiter (MRO) and the European Space Agency’s (ESA) Venus Express and Mars Express (MEX) missions. In addition to its current features, the platform is being enhanced with new functionalities, including the incorporation of geological maps [2] for targeted data queries and the visualization of subsurface radargrams from Mars using MARSIS data [3]. New Datasets: Current data integration efforts concentrate on lunar data gathered by various instruments on NASA’s Lunar Reconnaissance Orbiter (LRO), specifically the Lunar Orbiter Laser Altimeter (LOLA), the Narrow Angle Camera (NAC), the Wide-Angle Camera (WAC), and the Diviner Lunar Radiometer Experiment (Diviner), which are all being utilized for data analysis. Furthermore, the tool’s functionality is being enhanced through the integration of data derived from the Chandrayaan-1 mission’s Moon Mineralogical Mapper (M3), significantly broadening its scope and potential applications. The goal of these integrations is to deliver a suite of high-level products, including high-resolution digital terrain models (DTMs), detailed mineralogical maps, a variety of spectral indices, and other advanced datasets, all designed to facilitate comprehensive analyses of the lunar surface and subsurface features. Upcoming Pipelines: MATISSE’s future development includes the expansion of its scope to accommodate advanced data processing and analysis pipelines for diverse user bases. The use of these pipelines will enable researchers to examine a variety of mission scenarios, such as identifying suitable landing sites and analyzing subsurface structures through advanced radar and hyperspectral imaging. As an example, within a landing-site selection process, users can integrate slope and roughness metrics, communications line-of-sight calculations, solar flux estimations, and mineralogical or geological constraints to generate a comprehensive suitability map. Concurrently, advancements in radar and hyperspectral data processing will allow for the exploration of planetary surfaces and interiors at an unprecedented level of detail. These capabilities are being further enhanced through the development of a dedicated JupyterHub [3] platform. This environment affords users the adaptability to integrate MATISSE’s tools and datasets with userdefined code, third-party libraries, and personally uploaded data, thereby establishing a comprehensive planetary science workspace. Conclusions: In short, the combined capabilities of MATISSE's services and SSDC's vast data resources create a streamlined, collaborative environment that facilitates research workflows, thereby enabling researchers to effectively progress from initial data exploration to the final stages of mission deliverables. MATISSE accelerates processing, reduces errors, and adapts to diverse scientific and operational needs by offering a single platform for multiple data types. Using a web-based system makes planetary studies more efficient, customizable, and collaborative, proving MATISSE's value for current and future missions in data analysis, exploration, and discovery. Funding: This study has received financial support from the ASI-INAF agreement n. 2022-14HH.0". References: [1] A. Zinzi, M.T. Capria, E. Palomba, P. Giommi, L.A. Antonelli, (2016) Astronomy and Computing, Volume 15, 2016,Pages 16-28, ISSN 2213-1337, https://doi.org/10.1016/j.ascom.2016.02.006. [2] V. Camplone, A. Zinzi, M. Massironi, A.P. Rossi, F. Zucca, (2024) Astronomy and Computing, Volume 48, 2024, 100852, ISSN 2213-1337, https://doi.org/10.1016/j.ascom.2024.100852. [3] A. Zinzi et al., (2021), 5th Planetary Data and PSIDA 2021 (LPI Contrib. No. 2549), [3] Giacomo Nodjoumi, C H Brandt, J E Suárez-Valencia, et al. Collaborative and Reproducible planetary science through the Europlanet GMAP JupyterHub processing environment. ESS Open Archive . March 06, 2025. DOI: 10.22541/essoar.174129212.22376025/v1