Population change is a main driver behind global environmental change, including urban land expansion. In future scenario modeling, assumptions regarding how populations will change locally, despite identical global constraints of Shared Socioeconomic Pathways (SSPs), can have dramatic effects on subsequent regional urbanization. Using a spatial modeling experiment at high resolution (1 km), this study compared how two alternative US population projections, varying in the spatially explicit nature of demographic patterns and migration, affect urban land dynamics simulated by the Spatially Explicit, Long-term, Empirical 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 and domestic migration estimates, and (2) prevailing downscaled national-level projections (NP) 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 outcomes. Under the SP projection, urbanization displays more of an extensification pattern compared to the NP projection. This suggests that recent demographic information supports more extreme urban extensification and land pressures on existing rural areas in the US than previously anticipated. Urban land outcomes to population inputs were spatially variable 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.
Downscaling SSP-consistent global spatial urban land projections from 1/8-degree to 1-km resolution 2000–2100
Abstract Long-term, spatial urban land projections that simultaneously offer global coverage and local-scale empirical accuracy are rare. Recently a set of such projections was produced using data-science-based simulations and the Shared Socioeconomic Pathways (SSPs). These projections update at decadal time intervals from 2000 to 2100 with a spatial resolution of 1/8 degree, while many socio-environmental studies customarily run their analysis and modelling at finer spatial resolutions, e.g. 1-km. Here we develop and validate an algorithm to downscale the 1/8-degree spatial urban land projections to the 1-km resolution. The algorithm uses an iterative process to allocate the decadal amount of urban land expansion originally projected for each 1/8-degree grid to its constituent 1-km grids. The results are a set of global maps showing urban land fractions at the 1-km resolution, updated at decadal intervals from 2000 to 2100, under five different urban land expansion scenarios consistent with the SSPs. The data can support studies of potential interactions between future urbanization and environmental changes across spatial and temporal scales.
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- Award ID(s):
- 1757353
- NSF-PAR ID:
- 10331398
- Date Published:
- Journal Name:
- Scientific Data
- Volume:
- 8
- Issue:
- 1
- ISSN:
- 2052-4463
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1038/s41597-021-01052-0
