Exploring Urban Land Changes with Varying Population Projections
Urban land expansion varies with population projections; state-specific projections show more urban sprawl than previously.
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Urban areas are growing, and projecting how they will expand is a grand challenge. Our research examines how different population projections affect urban growth in the U.S. We find that even with the same global conditions, local population changes can lead to very different urban outcomes. Using a model called SELECT, we show that new population data suggests more urban sprawl into rural areas than previously thought. This means cities might spread out more, affecting land use and rural communities. Understanding these patterns helps us plan better for future urban development.
Our research explores how different population projections affect urban growth in the U.S. We use a model to see how cities might expand based on two types of population data: one that looks at state-specific trends and another that uses national averages. This is important because it helps us understand how cities might grow differently depending on local population changes. This study is one of the first to compare these two approaches using detailed models. Our findings can help other scientists project urban growth more accurately.
In our research, we explore how different population projections influence urban land development in the United States under the Shared Socioeconomic Pathways (SSPs). Using the Spatially Explicit, Long-term, Empirical City development (SELECT) model, we simulate urban land changes at a high resolution of 1 km, comparing two population projections: state-specific projections (SP) and national-level projections (NP). Despite identical global SSP constraints, our findings reveal that variations in population inputs can lead to significant differences in urban land outcomes. Under the SP projection, urbanization tends to show more extensification into rural areas compared to the NP projection, suggesting that recent demographic trends may support more extreme urban sprawl than previously anticipated.
Our study highlights the complex and non-linear relationships between population dynamics and urban land expansion. We observe that urban land development is not merely a linear product of population change but is influenced by a multitude of factors, including urban maturity and feedback mechanisms. This underscores the importance of incorporating spatial variations in population projections to accurately project long-term urban land patterns. Our findings emphasize the need for a nuanced understanding of the interplay between population growth and urbanization processes to improve future urban land simulation models.