Projecting the distribution of population is critical in supporting analysis of the impacts and risks associated with climate change. In this paper, we apply a computational algorithm parameterised for the UK Shared Socioeconomic Pathway (UK-SSP) narratives to create 1-km gridded urban land use and population projections for the UK to the end of the twenty-first century. Using a unimodal neighbourhood function, we model heterogeneity in urban sprawl patterns. The urban land use maps are used as weights to create downscaled population projections. We undertake a model uncertainty analysis using 500 simulations with varying parameter settings per UK-SSP. Results illustrate how sprawl can emerge from scenario conditions even when population numbers decline, and irrespective of socio-economic wellbeing. To avoid negative environmental externalities associated with uncontrolled sprawl, such as in UK-SSP5 and UK-SSP3, planning policies will be vital. Uncertainties about future population development in the UK are higher in rural areas than in urban areas. This has an effect on the competition for land and influences confidence in projections of broader land system change.