Spatial soil information is fundamental for environmental modelling and land management. Spatial representation (maps) of soil attributes (both laterally and vertically) and of soil-landscape processes are needed at a scale appropriate for environmental management. The challenge is to develop explicit, quantitative, and spatially realistic models of the soil-landscape continuum. Modern advances in soil sensing, geospatial technologies, and spatial statistics are enabling exciting opportunities to efficiently create more consistent, detailed, and accurate soil maps while providing information about the related uncertainty. The production of high-quality soil maps is a key issue because it enables stakeholders (e.g. farmers, planners, other scientists) to understand the variation of soils at the landscape, field, and sub-field scales. They can be used as input in environmental models, such as hydrological, climate or vegetation productivity (crop models) addressing the uncertainty in the soil layers and its impact in the environmental modelling. When the products of digital soil mapping are integrated within other environmental models it enables assessment and mapping of soil functions to support sustainable management. We welcome presentations that 1) demonstrate the implementation and use of digital soil maps in different disciplines such as agricultural (e.g. crops, food production) and environmental (e.g. element cycles, water, climate) modelling 2) advance the tools of digital soil mapping 3) investigate the philosophy and strategies of digital soil mapping at different scales and for different purposes. We also welcome contributions reporting the state of the art of soil property prediction from hyperspectral satellites, especially focusing on quantitative estimationsmaking use of data-driven approaches such as machine learning, and physically based modelling or the integration of both.