High-quality maritime spatial planning, coastal zone management, management of marine resources, environmental assessments and forecasting require comprehensive understanding of the seabed. Already in 2008 and in response to these needs the European Commission established the European Marine Observation and Data Network (EMODnet). The EMODnet concept is to assemble existing but often fragmented and partly inaccessible marine information into harmonized, interoperable, and publicly freely available data layers encompassing whole marine basins. As the data products are free of restrictions on use, the program is supporting any European maritime activities in promotion of sustainable use and management of the European seas.

Now in its fourth phase, the EMODnet-Geology project is delivering integrated geological data products that include seabed substrates, sediment accumulation and seabed erosion rates, seafloor geology including lithology and stratigraphy, Quaternary geology and geomorphology, coastal behavior, geological events such as submarine landslides and earthquakes, marine mineral resources, as well as submerged landscapes of the European continental shelf at various time-frames. All new map products are presented at a scale of 1:100,000 all over or finer but also at coarser scales to ensure maximum areal coverage. Thus partner updates of single-scale products at 1:250,000 and 1:1,000,000 were encouraged and these data products have been uploaded when available. A multi-scale approach is adopted whenever possible.

The EMODnet Geology project is executed by a consortium of 39 partners and subcontractors which core is made up by 23 members of European geological surveys (Eurogeosurveys) backed up by 16 other partner organizations with valuable expertise and data.

The EMODnet concept is, however, not restricted to the European seas only, as also the Caspian and the Caribbean Seas are included in the geographical scope of the EMODnet Geology project, and selected methods were shared with the EMODnet PArtnership for China and Europe (EMOD-PACE) project (2019-2022).

Discover Europe’s seabed geology at: https://emodnet.ec.europa.eu/en/geology

How to cite: Vallius, H., Kihlman, S., Kaskela, A., Kotilainen, A., Alanen, U., and Geology Partners, E.: EMODnet Geology – towards new standards on harmonizing marine geological data of the European seas - and beyond, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10770, https://doi.org/10.5194/egusphere-egu23-10770, 2023.

One of the biggest challenges temperate and tropical regions face is that dense forest covers much of the landscape, which can be problematic in lithological mapping. Synthetic Aperture Radar (SAR) data provides a window through heavily vegetated canopy and essential information about surface scattering that can be used to infer underlying lithology. This research proposes a new methodology for lithology classification based on Sentinel-1 SAR nested geospatial data and a hybrid Artificial Intelligence (AI) and Geographic Information Systems (GIS) technique. The purpose of this study is to demonstrate the ability of AI, GIS, and Sentinel-1 data to classify lithology in the heavy jungle of Amurang, Sulawesi, Indonesia. The results indicate the proposed method can accurately map 1:50,000 scale lithology and refine the Qv unit into young volcanic rocks (Qv) and young lava (Qvl) and further define the Qvl unit into three sub-units based on age where Qvls-1 is the younger and Qvls-3 is the older. Cross-validated results indicate our method identified lithology with an overall accuracy of 91.00%, a commission error rate of 3.03%, and an omission error rate of 2.15% compared to the 2006 X-band InSAR derived geological map of the Amurang, Sulawesi. The proposed method distinguishes and refines specific rock units and has the potential to semi-automate lithological mapping in heavily vegetated areas.

How to cite: Tighe, L., Ipranta, I., Singh, R., and said, T.: Artificial Intelligence-Based Lithology Classification Using Sentinel-1 Data in Amurang, Sulawesi, Indonesia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10791, https://doi.org/10.5194/egusphere-egu23-10791, 2023.

Remoteness and extreme environmental conditions characterize the North Victoria Land (NVL, Antarctica), located at the Pacific-Southern Ocean termination of the Transantarctic Mountains. Here only the 5% of the emerged land is ice free and available for direct geologic investigations.

Present knowledge of the NVL geotectonic setting derives from: i) geologic-structural data collected in the last decades from the sparse rock outcrops; ii) geophysical investigations performed in the framework of national and international scientific expeditions; iii) remote sensing analyses of radar and multi/hyperspectral data; and iv) integration of these multi-scale data.

Regionally sized, crustal scale faults crosscut the NVL from the Southern Ocean to the Ross Sea and represent inherited weakness zones that have been reactivated several times until Recent. These are both first-order faults, which separate crustal blocks (from W to E, the Wilson, Bowers, and Robertson Bay terranes), and second-order faults cutting through homogenous lithotectonic units. Due to the extensive ice cover, the real characteristics of these fault zones (e.g., geometry, thickness, persistence, locations of transfer zones and so possible associated fluid circulation) are still unclear, as well as the possible connections between the on-land and off-shore tectonic structures.

Here we present the intensity of brittle deformation distribution of an area of NVL where two main fault zones are supposed to interact (i.e., the Rennick and Aviator faults). The model map is derived by applying the parameter H/S, which quantifies the intensity of brittle deformation (H = fracture dimension and S = spacing among fractures belonging to the same azimuthal family; see Cianfarra et al. 2022).

The H/S map is derived from polymodal regression by full cubic surface of the mean normalized H/S. A total of 1224 H/S measurements from 113 sites were collected in NVL during the 2018 and 2021 PNRA campaigns in the framework of the G-IDEA and LARK PNRA-projects. The mean H/S for each site of field measurement was computed and then normalized by weighting the measured value by a factor proportional to the brittle strength of the various lithotypes (e.g., basalts-dolerites, well cemented sandstone-conglomerates, granites-migmatites, gneiss).

Preliminary results show: i) the presence of a relative maximum of the normalized mean H/S (Mt Jackman area) that could be linked to the Rennick and Aviator faults transfer zone; ii) a polymodal regression of the mean normalized H/S that matches the NNW-SSE orientation of the main regional mapped faults; iii) the increasing trend of the H/S in the northern area at the Pacific side of NVL suggesting a possible continuation and link between onshore and offshore tectonic structures (offshore investigations in NVL will be the target of the Authors in the next PNRA-BOOST 2023 Antarctic expedition).

The H/S map and its integration with remote observations and geophysical data represents a promising tool to locate ice-covered tectonic structures, define corridors of fracture damage zones and give new constrains for modelling any kind of fluid circulation.

Cianfarra et al. 2022, Tectonics 41, e2021TC007124, https://doi.org/10.1029/2021TC007124

How to cite: Cianfarra, P., Locatelli, M., Bagnasco, A., Crispini, L., Salvini, F., and Federico, L.: Modelling intensity of brittle deformation in ice-covered regions: a case study in North Victoria Land (Antarctica), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10960, https://doi.org/10.5194/egusphere-egu23-10960, 2023.

Here we present an open access GIS project associated to a structural database which includes the geo-structural measurements (over 6000) collected in the field during the past Italian PNRA (National Antarctic Research Program) scientific expeditions from the year 1988 to 2021. The targeted research area is the North Victoria Land (NVL), Antarctica, between the 70°-76° S latitude and the 159°-171° E longitude.

NVL is an area difficult to be accessed for direct geological studies on rocks due to the extensive ice/snow coverage (~5%) and few published studies with complete structural datasets are available so far.

Our database is organized in various fields which include: number/code of the expedition, date, code of the site of field structural measurement, geographical coordinates of the field measurement site, elevation, toponyms, lithological classification, geological unit, description of any collected sample, name of the field data collector, classification, attitude of measured structural element (strike/trend, dip/plunge, dip/plunge direction), local magnetic declination at the date of the field survey.  Fault attributes include fault type (normal, reverse, strike-slip), rake of the slickenlines and sense of motion. Attributes of the extensional fractures/joints also include their dimension (height, H) and spacing (S).

Moreover, the GIS project includes basic georeferenced maps such as: i) geological maps of NVL available in literature at 1:250.000 and 1:500.000 scale; ii) DEM of the bedrock and of the ice surface (from Bedmap 2); iii) the Radarsat mosaic of Antarctica; and iv) the MODIS mosaic of Antarctica.

This queryable database allows to perform multiple geostatistical analyses and realise geothematic maps such as: i) the spatial variability of the main azimuthal structural trends at the regional scale; ii) the intensity of brittle deformation quantified by the H/S parameter (see contribution of Cianfarra et al. in this meeting); and iii) thematic geostructural maps (e.g: maps of the foliation traces, of strain partitioning or fractures distribution).

These analyses, pivotal to better understand the tectonic framework of complex regions such as the NVL and to provide constraints supporting any geodynamic modelling, will greatly benefit from the extreme pliability and interoperability of such a database, which can be easily modified and expanded according to different scientific research needs by the production of newly derived data.

How to cite: Bagnasco, A., Cianfarra, P., Locatelli, M., Crispini, L., Balbi, E., Salvini, F., and Federico, L.: Geodatabase of structural data from North Victoria Land (Antarctica): a useful tool for geodynamic modelling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12547, https://doi.org/10.5194/egusphere-egu23-12547, 2023.

Increasing anthropogenic pressure in marine and coastal environments emphasizes the importance of the easily accessible, reliable, and suitable data on marine environment, to support conservation, research, and sustainable marine management decisions. The EMODnet (European Marine Observation and Data network) Geology project has been aiming to address this demand by collecting and harmonising geological data at different scales from all the European sea areas since 2009, at present with a collaboration of about 40 partners and subcontractors.

Seabed substrate data has been collected since the beginning of the EMODnet Geology project and it is one of the key elements shaping the physical structure of benthic habitats. In the project, national seabed substrate data is harmonised into a shared schema, based on the sediment grain size. However, there are some geologically and ecologically important seabed surface features, which cannot be explained only by grain size e.g., bioclastic features, moving sediment and FeMn concretion fields. Therefore, the project has also collected information on these features that partners have considered vital for the seabed environment. At best, this data could be a valuable addition to define e.g., geodiversity of the seabed environment when grain size distribution is insufficient.

The first review of the collected data aimed to identify and analyse the surface features, their occurrence and briefly discuss the prospects this additional information could provide. However, the development of a valuable surface features database requires further work, like developing guidelines concerning data collection methods, terminology, and classification. This work will need collaboration with different stakeholders and end users.

The EMODnet Geology project is funded by The European Climate, Environment and Infrastructure Executive Agency (CINEA) through contract EASME/EMFF/2020/3.1.11 - Lot 2/SI2.853812_EMODnet – Geology.

How to cite: Kihlman, S., Kaskela, A., Kotilainen, A., Alanen, U., Vallius, H., and Partners, E. G.: Analysing the added value of surface features information in the Seabed substrate data from the European sea areas - EMODnet Geology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13602, https://doi.org/10.5194/egusphere-egu23-13602, 2023.

We present our contribution to the European Marine Observation and Data Network (EMODnet) and the first comprehensive marine geological seafloor map compilation for Icelandic waters across an area of 764,000 km². Our study is based on a variety of datasets, such as multi-beam and high-resolution bathymetry, sub-bottom profile and 2D seismic reflection, seafloor samples, and core data. This forms the basis for this map compilation, as well as previously published research. Mapping the seafloor geology of Icelandic waters is highly variable and challenging including volcanic, tectonic, sedimentary, and glacial features. These include e.g., present-day active and dormant volcanic systems, eruptive fissures and craters, seamounts and ridges, faults and lineaments, submarine lava borders, landslides, hydrothermal vents, terminal moraines, the extent of the last glacial maximum, glacial streamlines, drumlins, and gravity channels elements. Iceland´s onshore volcanic systems are well characterized based on their distribution of volcanic and tectonic fissures and rock compositions, which continue across the Icelandic insular shelf and the country´s marine domain. On the Icelandic insular shelf and shelf slopes, 17 active volcanic systems have been defined. Seamounts and Seamount ridges were mapped as isolated topographic features rising from the ocean floor that are typically volcanic and/or tectonic in origin. More than 600 craters and 250 eruptive fissures have been mapped and are common within active spreading zones or along extinct ridges. Subaerial and submarine lava flows, primarily seen as pillow lava sheets, have been mapped along the Reykjanes- and Kolbeinsey Ridges, craters, and eruptive fissures. Distinct submarine pillow lava flows can be seen deeper than 400 m depth with flow lengths up to 8-9 km from the crater of origin, and an aerial extent of 45-50 km². Tectonic elements, fault zones, or fissures are prominent along the active spreading zones, and common across the insular shelf all around Iceland. They follow the primary structural grain of the mid-oceanic ridges north and southwest of Iceland and are predominantly active normal fault systems that are accompanied by earthquakes. Near the rift axes, these faults can form 20 km long and up to 400 m high continuous fault escarpments. Submarine landslides around Iceland are found in the fjords of east and west Iceland, but some are located on the insular slopes and on the Iceland-Faroe Ridge. The ages of these landslides are inferred to be of prehistoric age (>1200 years B.C.) as coastal areas became unstable after the last glaciation. Glacial landforms and erosional marks have been mapped along the entire insular shelf. This includes moraine ridges and glacial streamlines that hold information about past glacial movements and behaviour. This marine geological map compilation for Icelandic waters provides vital data input and starting point for future research and mapping projects that require maps such as seabed substrate, seafloor geology, coastal behaviour, geological events and probabilities, minerals, and submerged landscape map coverages.

How to cite: Erlendsson, Ö., Blischke, A., Hjartarson, Á., Óðinsson, D. Þ., and Vésteinsson, Á. Þ.: The Geological mapping of Iceland’s Insular Shelf and Adjacent Deep Ocean., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15536, https://doi.org/10.5194/egusphere-egu23-15536, 2023.

Data and information on the ocean floor is hardly findable scattered, rarely compatible, often inaccessible, and often usable only by insiders. The main reason for this situation is the inaccessibility of the ocean floor and the need to use and rely on mostly geophysical methods in order to create a geological map. Therefore, the ocean floor is by far not as thoroughly explored as on-shore areas: “we have better maps of the surface of Mars and the Moon than we do of the bottom of the ocean.” [Gene Feldmann, NASA, 2009: https://www.nasa.gov/audience/forstudents/5-8/features/oceans-the-great-unknown-58.html].

Thus, in 2009 the European Commission established the European Marine Observation and Data Network (EMODnet) programme, subdivided into seven thematic projects, one of which is EMODnet Geology. It aims to build digitally available map layers of the European Seas to be interoperable and generally and freely available. Within the EMODnet Geology the workpackage “Seafloor geology” (lead by BGR) compiles and harmonizes marine geological and geomorphological data from the EMODnet partners all over Europe and adjacent areas, to be made available on the EMODnet Geology portal [https://emodnet.ec.europa.eu/en/geology] and the BGR portal [https://geoportal.bgr.de].

These data contain information on geomorphology, age, lithology and genesis (process, environment) of each unit and encompass two relevant aspects of extreme environmental mapping:

a) they are often mapped in extreme environments such as mid-oceanic ridges, rift propagation zone, and subsea volcanic centres, e.g. the Grimsey lineament rift propagation zone located north-of Iceland; 

b) they contain information on past extreme environments, e.g. subglacial, volcanic or deep sea environments.

Underpinned by examples, this poster will present and discuss both aspects and outline the benefits of mapping in extreme environments also for general mapping projects such as EMODnet geology.

How to cite: Asch, K., Müller, A. M., and Blischke, A.: Ocean mapping: Finding and compiling spatial data on extreme environments – key information even for a general mapping project such as EMODnet geology, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16050, https://doi.org/10.5194/egusphere-egu23-16050, 2023.

Exploration Seismics is one of the most important geophysical methods that could provide insights of the Earth crust up to depths of several Kilometers. This approach has been used widely in many areas of the globe accumulating large datasets that allow to improve the knowledge of the Earth dynamics.

Providing access to recent and old datasets to the widest scientific community is of paramount importance to foster, as much as possible, collaborative research among scientists. In this, the possibility to find, preview and possibly process data directly on the web is extremely relevant.

National Institute of Oceanography and Applied Geophysics - OGS is deeply committed in developing a web-based framework named Seismic data Network Access Point (SNAP) (https://snap.ogs.trieste.it), that allows scientists to remotely explore data assets that have been acquired by OGS itself and by other research institutions. SNAP is used within several international data dissemination initiatives such as EMODnet, SeaDataNet, SCAR-SDLS and others.

These kinds of initiatives often focus on specific areas, such as for example the European Seas or Antarctica, that are located far from each other and that have different needs in terms of projections or bounding boxes. Finding a one-fits-all solution for web mapping and data access to georeferenced data in such diverse environments is not easy.

Polar areas, in particular, are as complex to handle as difficult to survey. At the same time these regions are of overwhelming importance for climate studies. The remoteness, extreme weather conditions, and environmental sensitivity of Antarctica make new data acquisition complicated and existing seismic data very valuable. It is, therefore, critical that existing data are Findable, Accessible, Interoperable and Reusable (FAIR). The aim of the SNAP framework and its implementations is to allow seismic data acquired in distant and different regions of the globe to be immediately accessible within a FAIR paradigm, offering all standard OGC compliant metadata models, and OGC compliant data access services.

We will present in detail the SNAP web-based framework in the light of Open Data and FAIR principles, and its planned future developments.

How to cite: Diviacco, P., Busato, A., Burca, M., Viola, A., and Potleca, N.: Bridging “Around the world in 80 days” and “Journey to the Center of the Earth”: web-based mapping of exploration seismics data around the globe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16497, https://doi.org/10.5194/egusphere-egu23-16497, 2023.

Seafloor mapping is essential for effective management and sustainable development of marine resources. Various attempts have been made to map the seafloor using single beam echo sounders, multi beam echo sounders, and side scan sonars. The purpose of this study is to map the sea floor using backscatter and bathymetry based on multi-beam echo sounders. For seafloor mapping, seafloor cover was defined as rock, gravel, sand, and mud according to the folk structure, and 135 grab data were collected for seafloor mapping and accuracy evaluation. For seafloor mapping, bathymetry depth and depth-based secondary products (aspect, curvature, slope, roughness, eastness, northness, mean, standard deviation) and backscatter intensity and secondary products that can be produced from intensity (mean, variance, roughness) was established. In addition, the output of the GLCM algorithm (angular second moment, contrast, dissimilarity, energy, entropy, homogeneity, max, mean, standard deviation) was constructed to extract various features of backscatter intensity. For seafloor cover, a random forest model, a machine learning technique that shows high performance in various fields, was selected, and the ratio of training and test datasets was selected as 8:2. To improve the performance of the random forest model, a hyperparameter was selected by applying a 5-fold cross validation and grid-search method, and the overall accuracy was 0.83.

How to cite: Son, S., Bae, J., Lee, D., Park, S. R., Seo, J. M., and Kim, J.: Seabed substrate mapping using MBES data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4796, https://doi.org/10.5194/egusphere-egu23-4796, 2023.