Building a 4D Voxel-Based Decision Support System for a Sustainable Management of Marine Geological Resources

Building a 4D Voxel-Based Decision Support System for a Sustainable Management of Marine Geological Resources

Vera Van Lancker (Royal Belgian Institute of Natural Sciences, Belgium), Frederic Francken (Royal Belgian Institute of Natural Sciences, Belgium), Lars Kint (Royal Belgian Institute of Natural Sciences, Belgium), Nathan Terseleer (Royal Belgian Institute of Natural Sciences, Belgium), Dries Van den Eynde (Royal Belgian Institute of Natural Sciences, Belgium), Lies De Mol (FPS Economy, Belgium), Guy de Tré (Ghent University, Belgium), Robin De Mol (Ghent University, Belgium), Tine Missiaen (Ghent University, Belgium), Vasileios Hademenos (Ghent University, Belgium), Marcel Bakker (Geological Survey of the Netherlands, The Netherlands), Denise Maljers (Geological Survey of the Netherlands, The Netherlands), Jan Stafleu (Geological Survey of the Netherlands, The Netherlands) and Sytze van Heteren (TNO - Geological Survey of The Netherlands, The Netherlands)
DOI: 10.4018/978-1-5225-0700-0.ch010


For sustainable management of marine geological resources, a geological knowledge base is being built for the Belgian and southern Netherlands part of the North Sea. Voxel models of the subsurface are used for predictions on sand and gravel quantities and qualities, to ensure long-term resource use. The voxels are filled with geological data from boreholes and seismic lines, but other information can be added also. The geology provides boundary conditions needed to run environmental impact models that calculate resource depletion and regeneration under various scenarios of aggregate extraction. Such analyses are important in monitoring progress towards good environmental status, as outlined in the Marine Strategy Framework Directive. By including uncertainty, data products can be generated with confidence limits, which is critical for assessing the significance of changes in the habitat or in any other resource-relevant parameter. All of the information is integrated into a cross-domain, multi-criteria decision support system optimised for user-friendliness and online visualisation.
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Mineral and geological resources, including fossil fuels and aggregates, can be considered to be non-renewable on time scales relevant for decision makers (e.g. Reid et al., 2010; Mudd, 2010). In the vast majority of places, they are more rapidly exhausted by humans than they can be replenished by nature, meaning that truly sustainable resource management is not possible (Prior et al., 2012). Comprehensive knowledge on the distribution, composition and dynamics of geological resources, therefore, is critical for developing long-term strategies for optimised resource use.

With growing land-use constraints and depletion of terrestrial aggregate resources, marine sand and gravel have gained importance (ICES, 2016). On a global scale, the stock for these widely demanded bulk resources may be assumed infinite (USGS, 2016). Regionally, though, exploitation is limited by a diversity of interacting social, economical, technological, geological and political factors (Habert et al. 2010). In a further constraint, legislation for the protection of the environment requires the assessment of a large number of conditions that need to be fulfilled for sand and gravel extraction to be permitted (Radzevičius et al., 2010; ICES, 2016). However, thorough assessment frameworks are most commonly lacking, and environmental impact assessments are rarely based on best available knowledge (Velegrakis et al., 2010).

In this chapter, an innovative way of dealing with a multitude of cross-disciplinary information in a resource-management context is presented. It discusses the workflow developed within the research network TILES (Transnational and Integrated Long-term Marine Exploitation Strategies, The aim of TILES is the development of a 4D (3D and time), voxel (3D pixel or cuboid) -based resource decision support system (DSS) containing tools that link 3D geological models, knowledge and concepts to numerical environmental impact models. The (DSS) will primarily serve as a tool to generate resource suitability maps. These maps are instrumental in answering questions regarding application-specific extraction demands and preferences, showing if these can be met and, if so, highlighting well-suited areas.

The study area comprises the Belgian and southern Netherlands part of the North Sea (further abbreviated as BPNS and sNPNS), in total ± 7400 km2. Today, most of the Belgian resources are extracted from sandbanks (Degrendele et al., 2010; Degrendele et al., 2014). In the Netherlands, sand is also extracted in other, usually deeper, morphological settings (Stolk & Dijkshoorn, 2009). From south to north, the area is marked by increasing resource availability. The BPNS is relatively depleted of extractable sand and gravel, with Quaternary sediments being only 10 m thick on average (Le Bot et al., 2005), and less than 2.5 m thick or even absent in many of the swales separating the tidal sandbanks. The sNPNS has only few areas with such limited resource availability, although gravel is rare. Just north of the study area, in the extraction pit for the latest Rotterdam Harbour extension, sand was extracted to about 20 m below the seabed (de Jong et al., 2014).

Figure 1.

The Belgian and southern Netherlands part of the North Sea, a typical sandbank environment in the Southern Bight of the North Sea, northwestern Europe

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