The transition towards a clean and low carbon energy system in Europe will increasingly rely on the use of the subsurface. Communicating the potential and limitations of subsurface resources and applications remains challenging. This is partly because the subsurface is not part of the world people experience, leaving them without reference frame to understand impacts or consequences. A second element is that the geological context of a specific area is very abstract, three dimensional, and hence difficult to correctly and intuitively disclose using traditional geological maps or models. The GeoConnect³d project is finalising the development and testing of a new type of information system that can be used for various geo-applications, decision-making, and subsurface spatial planning. This is being accomplished through the innovative structural framework model, which reorganises, contextualises, and adds value to geological data. The model is primarily focused on geological limits, or broadly planar structures that separate a given geological unit from its neighbouring units. It also includes geomanifestations, highlighting any distinct local expression of ongoing or past geological processes. These manifestations, or anomalies, often point to specific geologic conditions and therefore can be important sources of information to improve geological understanding of an area and its subsurface (see Van Daele et al., this volume, Rombaut et al., this volume ). Geological information in this model is composed of spatial data at different scales, with a one-to-one link between geometries and their specific attributes (including uncertainties), and of semantic data, categorised conceptually and/or linked using generic SKOS hierarchical schemes. Concepts and geometries are linked by a one-to-many relationship. The combination of these elements subsequently results in a multi-scale, harmonised and robust model. In spite of its sound technical basis, consultation is highly intuitive. The underlying vocabulary is of high scientific standard and linked to INSPIRE and GeoSciML schemes, but can also automatically, both visually and semantically, be simplified to be understood by non-experts. The structural framework-geomanifestations methodology has now been applied to different areas in Europe. The focus on geological limits brings various advantages, such as displaying geological information in an explicit, and therefore more understandable way, and simplifying harmonisation efforts in large-scale geological structures crossing national borders originating from models of different scale and resolution. The link between spatial and semantic data is key in adding conceptual definitions and interpretations to geometries, and provides a very thorough consistency test for present-day regional understanding of geology. As a framework, other geological maps and models can be mapped to it by identifying common limits, such as faults, unconformities, etc, allowing to bring together non-harmonised maps in a meaningful way. The model demonstrates it is possible to gather existing geological data into a harmonised and robust knowledge system. We consider this as the way forward towards pan-European integration and harmonisation of geological information. Moreover, we identify the great potential of the structural framework model as a toolbox to communicate geosciences beyond our specialised community. Making geological information available to all stakeholders involved is an important step to support subsurface spatial planning to move forward towards a clean energy transition. . This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 731166.
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RBINS Staff Publications 2021
Subtidal natural hard substrates (SNHS) promote occupancy by rich benthic communities that provide irreplaceable and fundamental ecosystem functions, representing a global priority target for nature conservation and recognised in most European environmental legislation. However, scientifically validated methodologies for their quantitative spatial demarcation, including information on species occupancy and fine-scale environmental drivers (e.g., the effect of stone size on colonisation) are rare. This is, however, crucial information for sound ecological management. In this investigation, high-resolution (1 m) multibeam echosounder (MBES) depth and backscatter data and derivates, underwater imagery (UI) by video drop-frame, and grab sediment samples, all acquired within 32 km2 of seafloor in offshore Belgian waters, were integrated to produce a random forest (RF) spatial model, predicting the continuous distribution of the seafloor areal cover/m2 of the stones’ grain sizes promoting colonisation by sessile epilithic organisms. A semi-automated UI acquisition, processing, and analytical workflow was set up to quantitatively study the colonisation proportion of different grain sizes, identifying the colonisation potential to begin at stones with grain sizes Ø ≥ 2 cm. This parameter (i.e., % areal cover of stones Ø ≥ 2 cm/m2) was selected as the response variable for spatial predictive modelling. The model output is presented along with a protocol of error and uncertainty estimation. RF is confirmed as an accurate, versatile, and transferable mapping methodology, applicable to area-wide mapping of SNHS. UI is confirmed as an essential aid to acoustic seafloor classification, providing spatially representative numerical observations needed to carry out quantitative seafloor modelling of ecologically relevant parameters. This contribution sheds innovative insights into the ecologically relevant delineation of subtidal natural reef habitat, exploiting state-of-the-art underwater remote sensing and acoustic seafloor classification approaches.
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