Spatial soil information is fundamental for environmental modelling and land use management. Spatial representation (maps) of separate 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 to be used as input in environmental models, such as hydrological, climate or vegetation productivity (crop models) while addressing the uncertainty in the soil layers and its impact in the environmental modelling. This contemporary research would greatly benefit from synergies between pedometrics and spectroscopy/remote sensing scientists. There is the need to create models linking soil properties with ancillary environmental variables, such as proximal and remote sensing data. Modern advances in soil sensing, geospatial technologies, and spatial statistics are enabling exciting opportunities to efficiently create soil maps that are more consistent, detailed, and accurate than previous maps while providing information about the related uncertainty. The pillars of this paradigm are: a) the link between spectroscopy and wet soil laboratory analysis, seeking for the best strategy to evolve soil quality analysis; b) the link between proximal and remote sensing, with soil analysis; c) the link between proximal/remote sensing and pedometrics for extrapolating relationships established at point support to the spatial and temporal extent covered by proximal/remote sensing. Examples of 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 are welcomed. All presentations related to the tools of digital soil mapping, the philosophy and strategies of digital soil mapping at different scales and for different purposes are welcome.