Science for policy 6: Urban planning: sealing the future of soil functions - datasets?

Abstract

This dataset is part of Deliverable and 5.3 and produced by the WP4 team of the Landmark H2020 project. It contains the following shapefiles: PO6_BAU_NoZoning_50.shp PO6_BAU_NoZoning_100.shp PO6_BAU_Zoning_50.shp PO6_Sprawl_Zoning_50.shp PO6_BAU_NoZoning_50.shp PO6_Compact_Zoning_50.shp PO6_Compact_NoZoning_50.shp The metronamica Model was applied on six scenarios with combinations of business as usual, suburban sprawl or compact city development which build on the socio-economic projections and density assumptions of the ESPON-ET2050 project, and use the land use allocation parameters from the RECARE and SoilCare Integrated Assessment Models. Spatial development (zoning) was for some scenarios restricted in high productive fields. The model results give probabilities (0 – 1) of urban development within the 1 km² cells. Based on these probability percentages the different soil functions are reduced (100% of the probability and 50% of the probability) compared to the current soil functioning and, for the 50% scenarios, partly replaced by low productive grasslands as gardens and other public greenery. Z-scores are calculated from the spatial SF maps for each of the environmental zones. These environmental zones are derived from the Metzger et al. (2013). The z-scores give the signed fractional number of standard deviations by which SF means for an environmental zone are above or below the mean value and allow us indicate which areas have a higher or lower soil function performance compared to the mean value. Z-scores from the current SF maps and scenario maps were then compared to each other to calculate the change in z-scores. This change in z-scores is given in the shapefiles and describes the relative change in soil function performance. Positive values indicate an improvement in soil functioning compared to the current situation, negative values a decrease. More information regarding calculation and interpretation of both this dataset and the soil function maps used to calculate the z-scores can be found in: Vrebos D., F. Bampa, R. Creamer, A. Jones, E. Lugato, L. O’Sullivan, P. Meire, R.P.O. Schulte, J. Schroder and J. Staes (2018). Scenarios maps: visualizing optimized scenarios where supply of soil functions matches demands. LANDMARK Report 4.3.  and  Jones A. et al. (2019). An options document to propose future policy tools for functional soil management. LANDMARK 5.3. All available from www.landmark2020.eu.