Angelo Pio Rossi

The Martian lava plains are characterized by their extensive, low‐relief surfaces, which are the result of numerous basaltic eruptions and feature a variety of volcanic landforms, including vents, cones, pits, and skylights. The combination of these features and impact craters yields a significant understanding of the planet's geological past and subsurface composition. However, the flat terrain presents a challenge to detailed morphometric analyses, while the unavailability of high‐resolution Digital Elevation Models (DEMs) complicates the precise estimation of radar‐based thicknesses and dielectric constants. To address these challenges, we investigated an ∼8,030 km ² area northwest of Ascraeus Mons within the Tharsis Region. Prior research documented Amazonian volcanic features in this region; however, precise thickness and permittivity values remained undetermined owing to insufficient surface features and limited exposures. An enhanced, multi‐scale neighborhood analysis method, adapted from terrestrial and Martian applications, was utilized to define the boundaries of a shallow lava flow sequence and identify three previously unmapped volcanic vents. Subsequently, all available subsurface sounding radar data in the region were analyzed using a simplified method. The results demonstrate that shallow, low‐relief lava flows overlie a series of laterally consistent subsurface units, suggesting that volcanic and sedimentary processes occurred in multiple phases. The combination of our unique morphometric methodology using radar sounding showcases the characterization of morphologically subtle features despite the constraints of available data. This study offers a methodological framework for the investigation of other low‐relief Martian regions, enhancing our understanding of the planet's volcanic and stratigraphic evolution.

Orbital remote sensing has shown that some regions of the ancient Martian crust contain hundreds of discrete terrains covered by chloride‐rich evaporites. In terrestrial evaporitic systems, evaporite sequences typically begin with the deposition of carbonates, followed by sulfates, and finally chlorides, a depositional sequence that has not yet been found on Mars. Instead, sulfate deposits are always separated spatially and temporally from chlorides, suggesting two different depositional regimes. Here, we present a model driven by the Martian chlorine geochemical cycle that allows the formation of chlorides whilst simultaneously inhibiting sulfate and carbonate precipitation. In this model, the chlorides are produced under reducing and acidic conditions. Chloride deposition was driven by hydrothermal alteration of the Martian crust associated with faults, followed by precipitation from ascending saline solutions along the tectonic conduits. These processes occurred under a relatively thick and reducing atmosphere (1–0.1 bar). The crustal circulation of chloride‐precipitating fluids may have been driven by tectonic suction and pumping processes. Parental brines from hydrothermal activity sourcing chloride might also have contributed to the sulfates found in Cross and Columbus craters of Terra Sirenum. Our study integrates orbital imaging, topography, and spectroscopy with geochemical modeling and terrestrial analogs. We propose that the Terra Sirenum chloride deposits derive from subsurface brines, with deposition driven using tectonic and hydrothermal processes. Under inferred reducing and anoxic conditions, chloride formed with minimal co‐precipitation of sulfates and carbonates. Unlike isolated chloride deposits confined to topographic lows, the Terra Sirenum chlorides are associated with linear features interpreted as faults.

JupyterHub is an open‐source system enabling multiple users to access individual computational environments. This facilitates collaborative development and execution of Jupyter notebooks, Python scripts, and other tools among researchers and educators through a unified interface. Through the integration of container technologies, including Docker, JupyterHub achieves seamless scalability for numerous users while maintaining efficient computational resource management. This flexible approach is especially useful in specialized areas like planetary data science, which requires robust and reproducible workflows to manage large volumes of mission data. The Europlanet Geologic MApping of Planetary surfaces (GMAP) project employs a Docker‐based JupyterHub deployment to centralize essential data processing tools, such as the Integrated Software for Imagers and Spectrometers (ISIS) and the NASA Ames Stereo Pipeline (ASP). These open‐source tools facilitate tasks ranging from image calibration and map projection to stereogrammetry and 3D modeling. The deployment of these elements within Docker containers facilitates simplified installation and consistent performance across disparate hardware configurations. The use of pre‐configured image formats within ISIS, ASP, and other GIS and Python libraries allows planetary scientists to efficiently process raw data into analytical products, including Digital Terrain Models. Additionally, JupyterHub's architecture enables secure collaboration via authentication methods (e.g., OAuth, GitHub), with concurrent provision for private and shared data directories. This integrated framework promotes reproducible research by streamlining the sharing of scripts, notebooks, and workflows. The GMAP JupyterHub platform significantly accelerates scientific discovery through the reduction of technical barriers, the promotion of standardization, and the provision of global access to planetary data science resources.

Lunar intrusive igneous domes have not been the center of much research in the past due to their rare occurrence on the lunar surface, and the difficulty in locating them. Most of the known structures were discovered using images with low illumination angles, including data from the Lunar Orbiter, telescopic images, and photos taken during the Apollo Missions. These intrusive domes are characterized by an oval shape and low slopes. We analyzed one of these systems, the Valentine domes, located near the rim of the western Serenitatis basin, with modern techniques and data sets from the Lunar Reconnaissance Orbiter (LRO) and Chandrayaan‐1 missions. We created a geostratigraphic map of the area, combining geomorphological and spectral classifications. The aspect map (direction of the slope) proved to be the most suitable product to locate and delimit these structures; using it, we identified a new dome southeast of the principal body, suggesting that the intrusive system is larger than previously thought. It was found that the three domes can be classified as laccoliths, and that several derived structures such as rilles, dykes, and secondary domes represent different stages of intrusive activity in the area. Based on crater counting analysis, we determined that the intrusive activity began after 2.98 ± 0.15 Ga and lasted at least until 1.88 ± 0.5 Ga ago.

Spectral indexes are tools widely used to analyze the composition of planetary surfaces. Many indexes have been formulated over the years to map the lunar surface, but there is no unified database for them. In this work we describe an Open‐Source Python package called MoonIndex, that recreates 38 indexes compiled from the literature, using data from the Moon Mineralogy Mapper (M³). The processing started with the filtering of the data cubes to reduce the noise, the continuum of the spectrum was then removed using a convex hull or a second‐and‐first‐order fit method. Later, the indexes were calculated, following as possible the original formulations. The results on spectral indexes calculated before the continuum removal were similar to those of the original formulations. Conversely, the results obtained for spectral indexes calculated after the continual removal were not always coherent. Some indexes, like the band depth, are especially sensitive to the removal method, as well as the derived band areas and asymmetries. We also recreated RGB composite maps, our results highlight the compositional patterns in a similar way as the ones in the literature, even if the color ramps can differ. The products of MoonIndex are open, ready for interpretation, versatile, consistent, and cross‐comparable.

Introduction: In the field of planetary remote sensing, terabytes of data from extraterrestrial planetary bodies are made available to the scientific community today. With the development of new missions, the volume and variety of these data continue to grow.This development has been largely facilitated through developments leading to higher integrated technology allowing to build compact and efficiently performing platforms and instrumentation. A likely other reason might be an increasing international competitive pressure which motivated new developments in sensor technology and mission designs. Along with the increase of raw data volume, the volume of derived research data continues to grow in parallel, albeit at a slower rate.While mission data, i.e. primary research data (PRD), as derived from instruments, are commonly well maintained within archives such as the Planetary Data System (PDS) and Planetary Science Archive (PSA), derived research data, i.e., secondary research data (SRD) might not always share the same fate. For an more user and object-oriented usage of mission data first efforts came up in the last years [1-3]. Scientific studies, resulting in further derived data do not often receive the same attention.In order to accomplish efficient research data management (RDM) for both kind of RD and to provide tools across research domains it is important to develop appropriate and effective structures. In that context, research data infrastructures (RDI) have the primary goal of collecting existing data under uniform guidelines and to make data accessible in defined ways. RDI initiatives supports the establishment of research management practices, including adopted metadata standards, research lifecycle and associated infrastructures. E.g. The European Open Science Cloud (EOSC) as RDI undertaking, "aims to federate existing and future RDI - across disciplines - under a single umbrella, and provides (open) services for the European researcher community." [4] They are targeted to provide faster and more efficient data access in order to pool resources and avoid duplication where redundancy is technically not needed.A large volume of RD that are derived in the field of planetary research carry an explicit spatial component through an absolute reference, or through relative location information, as inherent characteristics, which can thus be described as spatial data and spatial RD. These spatial (research) data serve as fundamental basis for further cartographic products and maps.Maps, as one example of SRD, have been an essential part of planetary research since the beginning of observation and they have been constantly refined and improved since then. Planetary maps range from image maps to topographic reference maps, to geologic and to landing-site maps. Their variety, however, is naturally limited due to the lack of anthropogenic overprint and lithologic diversity.In order to re-integrate these maps into the research-data life cycle [5] and to make them not only available for a sustainable reuse, but also to improve the associated information, further efforts are necessary which are outlined in the following sections.Aims: The overarching goal here is to develop a practical concept, and to address requirements to enable open, transparent and sustainable access to planetary maps as part of the open planetary spatial research data family. Therefore, approved and established environments serve as blueprint for our concept for an Open Planetary Map repository.We here refer to maps as conventional cartographic visualization products which contain a classical map layout composed of the main map contents (the topics), map frame, map grid information related to at least one cartographic reference system, map scale information, map title and map legend, as well as other map-related metadata information [6, 7]. These maps can be provided in different formats on various media.Method and Results: In order to assess the current situation and to find a strategy to close the planetary research-data cycle, we first need to analyze the main elements along its current research path. We here 1. identify how the current situation, including users (actors) and data flows, is constituted and how main processes are characterized. In step 2., additional as well as potentially alternative roles and data paths, respectively, are identified and further developed through user and system requirements. Finally, based on the assessment of the current situation and a requirement analysis, potential solutions are highlighted in step 3. that build upon existing Earth-based Infrastructure developments, especially the INSPIRE framework [8] or demonstrate which additional developments are required.Especially the adaption of spatial research infrastructure developments shows how the planetary community could benefit from an adaption of existing infrastructure environments in order toSummary: The aim of this study is to characterize the relationships between different interest groups (stakeholders) and products as well as processes, and to discuss how processes could potentially be optimized and streamlined in order to re-insert planetary maps (and research information) into a healthy and sustainable research cycle. Developments like this could build a thematic bridge to Earth-based RD repositories [9-11] in order to push the reuse of planetary maps forward. One way of realizing an approach targeted at improving the re-use of research data in the planetary sciences is by merging the existing alternatives and to integrate the structural benefits from the INSPIRE (or any other SDI) domain. The creation of an Open Map Repository as part of a Planetary Research Data Infrastructure is described in detail in [12], in particular with respect to the communication and participation, coordination and the technical implementation. References: [1] Laura, J.R., et al 2017. ISPRS Journal of Geo-Information 6, 181; [2]...

Introduction: One essential part of NASA´s planetary geologic mapping program [1] is to coordinate and standardize the geological map process and products in planetary science. This important role is taken by the Astrogeology Team as USGS since the early sixties.Within the scope of an EU project called PLANetary MAPping (PLANMAP, [2]), which ended this year, initial steps to develop complementary expertise in the EU was done. To continue addressing the major scientific and technological challenges facing modern planetary science and strengthen Europe´s position and the forefront of space exploration a new pan-EU infrastructure, the EUROPLANET 2024 Research Infrastructure (EPN-2024-RI), is coordinating mapping efforts in the EU and with international partners. One component of this 4-year-project is the Geologic MApping of Planetary bodies (GMAP). This aims to serve the European planetary community through an infrastructure to foster, support, and sustain the production of planetary geological maps and related products following standard procedures [e.g., 3]). In order to do so, GMAP is directly building on the PLANMAP work [2], and several partners and institutions with previous experience in planetary geologic mapping are involved. That means a planetary scientist can produce a geological map or a derived higher-level product through GMAP Virtual Access (VA) with the help and advice of the GMAP partner institutions, who will provide base-maps and technical aid as part of the Joint Research Activity (JRA). The maps will provide support for ongoing and future planetary missions, training activities, and non-standard science-driven mapping projects, such as space resource mapping.GMAP – motivation and focus: The primary focus of GMAP is to streamline the processes which are involved in the production of geological and geomorphological maps of planetary surfaces. Here, we are mainly collecting existent approaches and related documents which handle the standardization of GIS-based mapping processes to enable the European community in creating cartographic products. The aim is to describe, develop, store, combine (!), access, update, revise, and finally, visualize scientific cartographic products. As soon as these steps can be handled in well-defined workflow and distributed among researchers and mappers, the highest possible level of homogenization, and thus standardization, is reached. This is the essential step to use these research products as a basis for broader studies. During the first year, coordination activities targeted the planning and the initial setup of digital infrastructure services that will be needed for supporting VA and JRA activities. The domain europlanet-gmap.eu was acquired by GMAP and will serve as the entry point for presenting the GMAP initiative, collecting most notable resources, for users’ access, for providing basic guidance for publishing new maps, request support and contribute to the overall project. The website is built on the same open source Content Management System (WordPress, [4]) already employed for the main Europlanet website, on https://europlanet-society.org. The GMAP data portal (see figure 1, [5]) and additional services and tools are being setup.GMAP – requirements and developments: In order to extract the requirements to support the European community in streamlining their planetary geological maps, a document was produced during the last year of JRA activities. The document contains state of the art information in this field and addresses the geologic mapping and cartographic aspects of the various Solar System bodies.Geologic process-specific and body-specific best practice and published case studies are included in [1]. The approaches for two-dimensional mapping and three-dimensional geologic mapping and modelling are introduced, as well as the range of non-standard map types that are envisaged within GMAP activities.In particular the following main topics are in development: 1) a mapping guide with essential information for the GIS-based mapping process, including CRS symbology, metadata, and naming conventions; 2) mapping templates for GIS-based mapping and for final map layout, as well as instructions about naming conventions [6].Mapping review directions are indicated, as well data sharing, distribution and discovery. Proposed standards, best practices, and tools are based on those existing, as well as on additional or new developments and adaptations [e.g. 7]. The document will be periodically updated. GMAP – summary and outlook: The development of the GMAP data portal [5] was initiated, based on existing developments from PLANMAP. The availability of GMAP products and underlying datasets is going to be FAIR (findable, accessible, interoperable, and reusable [8]), as also recommended by the VA Review Board (see also [9]), and building on the practices of PLANMAP [10], see also e.g. [11]). The use of existing tools by NASA and USGS such as Integrated Software for Imagers and Spectrometers (ISIS, [12]), and Ames Stereo Pipeline (ASP, [13]) will be promoted. Moreover, in addition to the community support by the GMAP VA, interaction with the community via OpenPlanetary [14] is also planned. All further information and current developments are available via [15] and [16].Acknowledgments: GMAP and Europlanet 2024 RI have received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871149.References: [1] Astrogeology Team at USGS, https://www.usgs.gov/centers/astrogeology-science-center, [2] https://planmap.eu/, [3] Nass, et al., (2020) Standard definition Document 1st iteration, available online at https://www.europlanet-gmap.eu/about-gmap/deliverables, [4] https://de.wordpress.org/, [5] GMAP data portal, available online at https://data.europlanet-gmap.eu, [6] GMAP Consortium (2021) GMAP wiki documentation and service pages, available online at...

Introduction: The Space Science Data Center (SSDC) developed MATISSE (Multi- purposed Advanced Tool for the Instruments for the Solar System Exploration, [1]) webtool, whose v2.0 update [2] is available at https://tools.ssdc.asi.it/Matisse/, which allows access to data of the planetary exploration missions.The MATISSE tool uses some protocols provided by the Virtual European Solar & Planetary Access (VESPA), including EPN-TAP, and allows access to a series of services without necessarily having to download the data, but view the maps directly online.In this context the work here presented points at improving and expanding the functionalities of the MATISSE tool to the planetary geology, by including some already published geological maps. These will be essential in order to make MATISSE a useful tool for the analysis of planetary surfaces.MATISSE for planetary geology: The geological maps involved in this project will be of fundamental help to the scientific community in the geological characterization of landing sites and to obtain useful information for the study of planetary bodies surface.The good choice of the landing site, which satisfies both engineering and scientific requirements, represents one of the key points for the success of a space mission.For example, the identification of landing sites, of particular geological / mineralogical interest, will be carried out thanks to data fusion techniques between visible images and infrared spectroscopic measurements. The tool in question will give the user the opportunity to observe the area in question integrating data of multiple sources.MATISSE will also be able to carry out geomorphological analysis and morphometric products (e.g. slopes, relief, roughness index) which will allow a complete investigation both from the geological and engineering point of view.The geological maps will be integrated with mineralogical maps, obtained using infrared spectroscopic data.In collaboration with PlanMap and GMap teams we are currently working to include Martian, Hermean and Cerean surfaces so that both recently ended missions (e.g., NASA’s Dawn) and missions still not in their scientific phase (e.g., ESA’s BepiColombo) would benefit for this work. Work methodology: The geological maps of interest will be downloaded in appropriate format, so that every polygon representing a geological unit can be separately inserted into the geospatial database of MATISSE and be easily retrieved by the user.In particular, the user can choose one or more of the polygonal units as input for the geographical query after selecting the target and the instruments of interest. In this way the MATISSE capabilities can be fully exploited even trough geological oriented requests.Here are some examples of areas that we have analyzed on the Martian surface, with the collaboration of the PLANMAP team. These sites, Firsoff Crater and Commelin Crater, are located in Arabia Terra region. After a careful geological analysis of the two craters, similar morphological characteristics were identified [3].After starting the query, the user will see the area with the selected lithologies displayed (figure 1) and can carry out appropriate analyzes.Expected outcomes: We plan to make available the first release of MATISSE with geological maps in the next months, even if starting with only limited capabilities.The inclusion of these functionalities in the tool could produce a sensible step forward in the study of planetary geology, with the possibility of better exploiting different datasets and taking also into account the collaboration of different teams already leaders if this field.Another goal will be to expand the use of the tool, making it similar to the Geographic Information System (GIS). We will expand the possibility of selecting specific areas to be analyzed on the base of the geographical position of the data and the pertinence to specific geological units. It will be also possible to obtain topographic profile and select multiple data to be simultaneously observed. All these analyzes will be performed directly on 3D models.References: [1] Zinzi A. et al. (2016) Astron. Comput., 15, 16-28. [2] Zinzi A. et al. (2019) EPSC-DPS Joint Meeting 2019, id. EPSC-DPS2019-1272. [3] Pondrelli M. et al. (2010) Earth and Planetary Science Letters, 304, 511-519.

Introduction: OpenPlanetary, or simply "OP", is an international non-profit organisation that promotes open research in the planetary science and exploration communities: sharing ideas and collaborating on planetary research and data analysis problems, new challenges, and opportunities [1].OpenPlanetary started in 2015 as a way for participants of the ESA’s Planetary GIS Workshop to stay connected and exchange information related to and beyond this workshop. It expanded further by playing a similar role for the second USGS-hosted Planetary Data Workshop (PDW) in 2017. OpenPlanetary has continued to support the biannual PDW and provides a more persistent forum for participants to highlight presented topics and discussions from the workshops.In 2018, we established OpenPlanetary as a non-profit organisation (Association under 1901 French Law, [2]) in order to provide us with a legal framework to sustainably fund our community framework, projects and activities, and to better serve the planetary science community as a whole. OpenPlanetary is governed by a Board of Directors, elected for two years, which (1) define the policy and general orientation, (2) initiate, endorse, lead, or contribute to the projects and activities, and (3) can make use of the funds of the Association for any endorsed project or activity; the Bureau contains a 3-person subset of the Board members (a president, treasurer, and secretary) and serves as the executive body of the Association.Mission: Our mission is to promote and facilitate the open practice of planetary science and data analysis for professionals and amateurs. We do so by organizing events and conducting collaborative projects aimed at creating scientific, technical and educational resources, tools and data accessible to all.Members and Membership: With currently 300+ members across the world, OpenPlanetary membership is free and open to research and education professionals: scientists, engineers, designers, teachers and students, space enthusiasts and citizen scientists [3]. Although the early membership had a strong representation in planetary surface and mapping sciences, OpenPlanetary has expanded and is intended to serve as an “umbrella” for all communities of planetary data and tool users, producers or providers across scientific disciplines, space missions or working groups.Collaboration Platform: Our collaboration platform mainly consists of fully-featured Slack and Github instances. OP members use OP Slack workspace to stay connected and have real-time discussions with other members [4], and are entitled to request admin rights to host and manage open source projects on OP Github organization [5].Online Forum: We provide a public online OP Forum for research professionals and amateurs across all planetary science disciplines and communities to find help, share and discuss data, tools and resources [6]. While OP Slack is considered for the more informal discussions, the OP Forum is intended to post Q/A and discussion ”gems'' from OP Slack, or any resources that would help a broader community (eg: a short tip, a handy how-to guide or a list of curated resources), and that would benefit from having a permanent web-presence and being discoverable by search engines.Data Cafés: Since 2017, we have organised Data Cafés at scientific conferences for people to meet, share, discuss and solve common challenges and issues related to planetary data handling and analysis. These events follow an "unconference" format allowing and encouraging anyone to propose a topic and lead a group activity (eg: demo, tutorial, hack), or simply to ask for help [7].Online Events: Unable to continue with the in-person Data Cafés in 2020, we started hosting virtual online events: (1) OPvCon in June 2020 was our first free virtual conference, scheduled in place of the cancelled Planetary Science Informatics and Data Analytics Conference (PSIDA). It consisted of lecture-length talks from invited speakers, networking opportunities, workshops and tutorials, and a hackathon [8], and (2) since March 2020, we have hosted weekly OP Lunch Talks to present and discuss technical topics of interest to the planetary science community [9]. Most of these events are recorded and made publicly available on YouTube. They now represent a substantial collection of high-quality informational resources and training videos on diverse topics related to planetary science [10].Community Projects: Our flagship project is OpenPlanetaryMap (OPM), an open planetary mapping and social platform and effort to foster planetary mapping and cartography on the web for all [11]. We also support PlanetaryPy, a community effort to develop a core package for planetary science in Python and foster interoperability between Python planetary science packages [12]. A number of other projects not strictly homed under the OP umbrella have arisen from collaborations fostered in OP Slack or during OP Lunch discussion sessions.Outlook: We held our first yearly OpenPlanetary General Assembly in December 2020 [13], during which a new Board of Directors was elected. Our main focus within the next couple of years is on (1) consolidating and expanding OP Lunch and other virtual activities, (2) increasing the usage and impact of the OP Forum for all communities (eg: Planetary Spatial Data Infrastructures (SDI) communities), and (3) identifying sustainable funding opportunities. References: [1] https://www.openplanetary.org, [2] https://www.journal-officiel.gouv.fr/associations/detail-annonce/associations_b/20180009/457, [3] https://www.openplanetary.org/join, [4] http://openplanetary.slack.com, [5] https://github.com/openplanetary, [6] https://forum.openplanetary.org [7] https://github.com/openplanetary/op-data-cafe, [8] https://www.openplanetary.org/vcon, [9] https://www.openplanetary.org/vlunch, [10] https://www.youtube.com/openplanetary, [11] https://www.openplanetary.org/opm, [12]...

Geological maps have been historically a central part of the geological knowledge acquisition process: they are used to summarize all the relevant information of a site of interest and they provide the cornerstone for decision making, scientific discovery and three-dimensional geological modeling.Depending on the scope of the geological survey the cartography can depict different types of content: whether lithostratigrapy, chronostratigrapy, morphology, or other criteria are considered, the building blocks of a geological map is the geological unit, as the base element used to subdivide a region into geologically homogeneous patches of terrain. Digitized maps are normally represented within GIS software as polygonal layers.A common approach for mapping has been to directly draw polygons representing the different units on the map: although this approach appears the simplest one, it poses several issues in terms of topological consistency of resulting maps, especially when it comes to updating existing cartography. Furthermore, from a purely information science standpoint this representation, although useful for visualization, is inherently redundant, defining the same boundary geometry two times for each polygonal couples in contact.Editing polygonal layers is inherently problematic because vertex and edge correspondence between polygons in contact must be enforced by the operator. Although most GIS software implements appropriate tools (for editing and for topology validation) which can help in achieving error-free polygonal layers, the burden of using them is left to the operator and it is not enforced by the data format itself.A better solution for generating topologically-consistent geological maps consists in tracing the contacts separating the units, and then transforming them into polygonal layers (by using what is often known as a “polygonize” operation) for map finalization (see Figure 1).Figure 1: Generation of a consistent polygonal layer by polygonize operation, this can be performed by any GIS and is suggested as a good practice in geological map generation. A line layer is used for tracing the contacts between the different units and a point layer is also needed to define attributes for the polygons.This approach is also more similar to the geological reasoning that is performed when mapping, especially when remotely -sensed imagery is used (as in planetary mapping): the operator tries to identify the boundaries between different terrains rather than directly defining the area covered by the units themselves. This strategy hasve the clear benefit of making editing the map easier but, even when employed by the operator, the original layers (contact lines and points) are rarely or never distributed to the public, making it impossible to apply this method when updating already existing maps.In order to solve this problem we implemented a python module and a QGIS plugin called Mappy which is mostly based on already-existent modules as numpy (Oliphant 2006), geopandas (Jordahl et al. 2019), and topojson (Bostock 2017). Mappy implements the backwards transformation of the polygonize operation decomposing a polygonal layer into boundary lines and a point layer that contains the attributes of the original polygonal layer (the forward transform is also implemented). The input polygonal layer is first transformed into a topology-aware representation via topojson: first the intersection points are detected and then the polygons boundaries are split at those points, creating a list of arcs: each representing an unique portion of a contact line (Figure 2). Topojson representation can also account for rounding errors in the nodes coordinates and makes it possible to also consistently apply line-simplification methods (e.g. to reduce the number of nodes) while maintaining the original topology.Figure 2: The inverse operation of a "polygonize" operation as performed by mappy. a) the input polygonal layers with attributes; b) the topojson representation as list of arcs (each polygon is then just a list of arcs in the right order); c) the arcs are aggregated to create a representation more suitable for geological editing; d) point are positioned in the visual center of each polygon and the attributes are then transferred.Although being topologically sound, the topojson format of a polygonal layer is not the best suited representation for editing geological maps: given each line is split at the intersection points (Figure 2b) a contact might be split in a number of segments (i.e. when a contact separates one unit from several others) making it more difficult to edit the contact of a specific unit. For this reason, Mappy further processes the lines to aggregate several continuous arcs into a single polylines (Figure 2c).For each polygon an indicator point is then automatically computed to be in its visual center and the original attributes of the polygons are transferred to it. The points are placed by using the “polylabel” method provided by shapely module (Gillies and others 2007).The described approach has been then implemented in a standalone module that is also accessible from a QGIS plugin enabling easy transformation of any existing map into a line and points representations and vice-versa, therefore simplifying the process of editing and topology checking of existent geological maps.Acknowledgments: This research was supported by European Union’s Horizon 2020 under grant agreement No 776276- PLANMAP.References:Bostock, Mike, 2017 TopoJSON. URL: https://github.com/topojson/topojson-specification.Gillies, Sean, and others, 2007 Shapely: Manipulation and Analysis of Geometric Objects. toblerity.org. https://github.com/Toblerity/Shapely.Jordahl, Kelsey, Joris Van Den Bossche, Jacob Wasserman, et al., 2019 Geopandas/Geopandas: V0.4.1. Zenodo. https://zenodo.org/record/2585849, accessed June 29, 2020.Oliphant, Travis, 2006 NumPy: A Guide to NumPy....