DSM Products at Continental Scale: How to Assess These?

Many Digital Soil Modelling (DSM) products have been generated for diverse regions, countries and continents. While most of these products provide some accuracy metrics, a few also incorporate assessments of uncertainty. The current uncertainty estimates for DSM products often fail to represent elements that are essential for evaluating the suitability of a map for a specific application. For instance, different models can have very similar accuracy metrics but produce different soil-landscape patterns. It is important to be able to evaluate the accuracy of the patterns as well, current accuracy metrics do not do this. Additional metrics could be defined that are able to do this such the ‘area of applicability’, i.e. the area in covariate space where the model learns about relationships based on the training data) and the landscape heterogeneity both in the landscape itself and in covariate space. This study delves into the integration of the aforementioned elements into an assessment of DSM uncertainty at the continental scale. Europe was used as test area, incorporating input observations from EU-LUCAS datasets. A covariate space encompassing the soil forming factors as defined by the SCORPAN model served as a basis for fitting the necessary models for soil products.. We characterized the spatial heterogeneity of both the landscape and the covariate space by employing commonly employed landscape metrics. The findings offer practical insights on how to integrate these components to produce more reliable products for stakeholders.