Assumptions & limitations for soil degradation

Before turning to the limitations of specific datasets, a few general points apply across the risk assessment for soil degradation:

• Not all types of soil degradation are spatially mapped.
• The datasets mostly reflect the current situation, although some are based on older data and may not capture recent changes.
• This risk assessment only allows for a first indication, not a complete or detailed one.
• The spatial resolution of some datasets is relatively low, making it difficult to assess risks at a specific site or asset level.
• Soil degradation is widespread in urban areas, but complete datasets are scarce and there is considerable variation.
• Soil health is multidimensional: soil properties interact, and individual data layers provide only a partial picture. Meaningful interpretation therefore requires considering the soil system as a whole, as different layers may complement or contradict one another.

In addition, several datasets carry limitations specific to how they were constructed:

• The datasets Soil organic matter content at different depths and Soil acidity levels are both predictions based on modelled variables, and may therefore deviate from the actual situation on the ground.
• The datasets Soil ecological capital, unaffected by diffuse soil contamination, Self-cleaning capacity in the topsoil, and Natural water regulation in the soil all reflect only the topsoil. The Soil ecological capital dataset is additionally based on only four metals (lead, zinc, copper and cadmium), assumed to contribute most to diffuse soil contamination in the Netherlands.
• The Natural supply of nutrients in the soil dataset is indicative and covers only the top 20 centimetres of the soil.
• The dataset on Land cover is a detailed and generally reliable dataset, though misclassification may occur for small-scale elements, for compacted soil (where bare soil can be difficult to distinguish from paved surfaces), and for hedges and other narrow, linear features.