While geological models traditionally focus on the natural status of the underground, the shallow subsurface has been significantly altered by human activities over centuries. Particularly in urban contexts, ground has been raised, reworked, filled-in or disturbed in other ways. The rationale behind these alterations is as varied as the characteristics of the associated anthropogenic deposits: large-scale structures such as residential and industrial areas built on extensive sheets of filling materials or reclaimed lands are intertwined with smaller-scale features related, for example, to road and railway infrastructures, dikes or landfills. Their composition is equally diverse, ranging from displaced natural materials, such as crushed rocks, gravel, sand or clay, to artificial substances like recycled steel slags, concrete or rubble, or mixtures of these. Gaining knowledge on the presence and characteristics of such deposits is highly relevant, as their physical and chemical behaviour may differ significantly from those of natural deposits. The significance of anthropogenic deposits is increasingly recognized in urban geology. Resolving the geometry and properties of the urban shallow subsurface is essential for anticipating associated risks, for example dealing with pollution, ground stability or distorted water infiltration patterns. Anthropogenic deposits are, however, often scantily archived in permit documentation or represented on (geological) maps. Within the GSEU (Geological Service for Europe) project, the GSB is contributing to the task to develop a common, international vocabulary to describe all aspects of anthropogenic deposits, allowing standardised representation and characterisation in geological models. In parallel, VITO is developing shallow subsurface urban models for the Flemish government (VPO) within the VLAKO-framework, such as the published model of the Antwerp harbour and city. As the anthropogene inherently is part of these models, we are always aiming to better incorporate these deposits into the models. However, modelling the anthropogene presents unique challenges due to its high-resolution variability, scarcity of input data, and dynamic nature. It requires an approach that differs radically from traditional geological modelling techniques, in which depositional concepts related to the sedimentational or structural environment can be incorporated. In this presentation we will outline how we integrate various 1D, 2D and 3D sources to identify and characterize anthropogenic deposits and incorporate these insights in a 3D geological model of the anthropogene. This methodology is applied to the urban periphery of Brussels, where a new 3D geological model is being developed to support infrastructure projects and urban planning with special focus on the ring road (R0) of Brussels. Secondly, we will evaluate current lithological standards, vocabulary and stratigraphic approaches to characterize anthropogenic deposits. We will discuss their applicability in Flanders with practical examples from the periphery of Brussels. Ultimately, improving the representation of the anthropogene in geological models will significantly enhance their utility for urban planning, environmental management, and the sustainable utilization of the subsurface in urban areas.
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RBINS Staff Publications 2024
1.Migratory species depend on ephemeral environmental conditions; thus, species distribution modelling (SDM) must incorporate phenological changes along migratory routes. Our overarching goal was to model habitats for three waterfowl species migrating through Eurasian grasslands (red-breasted goose [Branta ruficollis], taiga bean goose [Anser fabalis fabalis] and Bewick's swan [Cygnus columbianus bewickii]) while accounting for ephemeral environmental conditions. Our objectives were (a) to develop a workflow of mapping ephemeral environmental conditions, (b) model habitats for the three species and (c) evaluate the protection status of habitats in natural and agricultural landscapes. We expected water availability, particularly ephemeral spring waterbodies, to strongly influence these species' distributions. 2. We utilized MODIS data for phenological synchronization of Landsat images to create species-and season-specific metrics and land cover maps. We used Landsat-derived environmental variables, elevation and bird GPS locations in Maxent SDM. We compared locations of modelled habitats, protected areas and Ramsar sites. 3. Our land cover maps had an overall accuracy of 0.92–0.95 and captured ephemeral water extent during these species' migrations. All models had AUC scores of 0.89–0.94; distance to water, land cover and elevation were the most important variables. Modelled habitats were distributed unevenly and occurred in both natural and agricultural landscapes; 40%–76% fell within croplands. Although most croplands provide a rich food supply, their value as waterfowl habitat critically depended on water availability. Approximately 22% of potential habitat in the natural landscape, but only 3% in croplands, had some level of protection.
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RBINS Staff Publications 2025
