PNNL

Abstract

Pathways (SSPs), can have dramatic effects on subsequent regional urbanization. Using a spatial migration, affect urban land dynamics simulated by the Spatially Explicit, Long-term, Empirical and domestic migration estimates, and 2) prevailing downscaled national-level projections (NP) outcomes. Under the SP projection, less urban land expansion is expected in urban areas and than previously anticipated. Urban land outcomes to population inputs were spatially variable population projections, varying in the spatially explicit nature of demographic patterns and Population change is a main driver behind many societal and environmental issues, including urban land use and land cover (LULC) change. In future scenario modeling, assumptions regarding how populations will change locally, despite identical global constraints of Shared Socioeconomic modeling experiment at high resolution (1-km), this study compared how two alternative US City development (SELECT) model for SSP2, SSP3, and SSP5. The population projections included: 1) newer downscaled state-specific population (SP) projections inclusive of updated international agnostic to localized demographic processes. Our work shows that alternative population inputs, even those under the same SSP, can lead to dramatic and complex differences in urban land more urban land expansion in rural areas than under the NP projection. This suggests that recent demographic information supports more extreme urban extensification in rural areas in the US where areas in close spatial proximity showed divergent patterns, reflective of the spatially complex urbanization processes that can be accommodated in SELECT. Although different population projections and assumptions led to divergent outcomes, urban land development is not a linear product of population change but the result of complex relationships between population, dynamic urbanization processes, stages of urban development maturity, and feedback mechanisms. These findings highlight the importance of accounting for spatial variations in the population projections, but also urbanization process to accurately project long- term urban land patterns.