Urban Scaling as Validation for Predictions of Imperviousness From Population. Issue 23 (28th November 2020)

• Record Type: Journal Article
• Authors: Brelsford, Christa; Coon, Ethan T.; Moran, Edward; Allen‐Dumas, Melissa
• Is Part Of: Geophysical research letters. Volume 47:Issue 23(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-11-28
• Subjects: Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2020GL089742
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Strategies for creating quantitative projections for human systems, especially impervious surfaces, are necessary to consider the human drivers of climate and ecosystem change. There are models that generate predictions of how impervious surfaces may change in response to different potential futures, but few tools exist for validating those predictions. We seek to fill that gap. We demonstrate a statistically robust sublinear scaling relationship between population and urban imperviousness across a 15 year history. We show that Integrated Climate and Land‐Use Scenarios (ICLUS) urbanization projections are also consistent with theory. These results demonstrate a theory that can be used to validate other models' predictions of urban growth and land cover change, analogous to the ways in which allometric scaling laws in biology have been used to validate process‐based models of ecosystem composition under different climate scenarios. Plain Language Summary: The decisions human organizations like cities or countries make can have a big influence on the environment, and the environment can influence our decisions. Scientists have some tools for modeling long‐term interactions between cities and the environment. It is hard to learn if these tools are working, because even if we know how a particular decision–if made–would influence the environment, we are not good at predicting what decisions will be made. We show that there is a specific mathematical shape to the relationship between a city's population and the total built‐up area: things like roads, parking lots, or buildings. This mathematical relationship shows us that in cities with larger populations, there is less space available per person and so built‐up areas are more intensely used. We then test whether other researchers' predictions about interactions between urban population and built‐up areas predict that these places will be more intensely used, like we showed. We show that the other researchers' predictions do correctly represent some important things we know about cities. This helps us know more about how reliable our predictions of interactions between human organizations and the environment might be. Key Points: Urban Scaling theory can validate process‐based models of urban growth, measured by impervious surface area ICLUS projections are consistent with urban scaling theory