PNNL

The Science
Researchers created a data set on historic urban area growth using satellite observations and then developed models that project future growth at the country level. They used the models to project country-level urban extents under five different future scenarios of socioeconomic change through 2100.

The Impact
This new data set can be the foundation for various global change studies; for example, simulating urban sprawl, modeling multisector dynamics, and investigating the effects of urbanization on air quality, and human health.

Summary
Better understanding of the potential growth of urban areas at the national and global levels is important for exploring the linkages between urban systems, other human systems, and the environment. In this study, researchers at the Department of Energy’s Pacific Northwest National Laboratory and Iowa State University developed urban area growth models for each country using the time‐series dataset of global urban extents (1992–2013), and projected the future growth of urban areas under five Shared Socioeconomic Pathways (SSPs), which are reference pathways depicting plausible alternative trends in the evolution of society and ecosystems through 2100. Global urban area is projected to increase by roughly 40–67% under the five scenarios by 2050 relative to the base year of 2013, and this trend would continue to a growth ratio of more than 200% by 2100. Although developing countries would remain leading contributors to the increase of global urban areas in the future, they may exhibit different temporal patterns, i.e., plateaued or monotonically increasing trends. Our urban area dataset is the first country‐level urban area projection consistent with the five SSPs, between 2013 and 2100. Several types of predictive global change studies can be built on this dataset, e.g., urban sprawl simulation, multisector dynamics modeling, and investigating the effects of urban growth on air pollution and public health.

PI Contact
Mohamad Hejazi, Pacific Northwest National Laboratory, Mohamad.Hejazi@pnnl.gov  

Funding
This work was supported by the U.S. Department of Energy Office of Science, as part of research in the MultiSector Dynamics Earth and Environmental System Modeling Program, the NASA ROSES LULC Program and the NASA ROSES INCA Program. Jiyong Eom was also supported by the Ministry of Environment of Korea through the Climate Change Correspondence Program.