Qingxu Huang shares insights from a recent article published in Nature Scientific Data on updating global urbanization projections under future scenarios of socioeconomic and climate change. The study was conducted in collaboration with Raya Muttarak from the IIASA Population and Just Societies Program.

Urbanization is a complex process involving the migration of people from rural to urban areas, land use change from rural to urban landscapes, and socioeconomic changes in living and consumption behaviors. While this process can promote social and economic progress, it also exerts substantial pressures on ecosystems and the environment. Therefore, understanding the level of urbanization of a country and how it will evolve in the future is crucial for policy planning.

The share of the population living in urban areas is a widely used indicator to determine an area’s urbanization level, which is in turn an important driver for socioeconomic changes and climate change. Previous studies from the Population Division of the Department of Economic and Social Affairs of the United Nations and the National Center for Atmospheric Research, USA, have projected the trends of urbanization levels by 2050 and 2100, respectively. However, they adopted a global uniform method based on the difference in urban and rural population growth rates over the sampled countries, which may result in inaccuracies between the estimated values and the actual values for some countries.

In our latest paper, we addressed this issue by establishing country-specific logistic fitting models for over 180 countries and regions, which allows us to better capture the distribution of various concentrations of people within an area in urbanization trajectories. The updated projections of urbanization levels from the 2015 to 2100 dataset provide estimates for five socioeconomic narratives representing future socioeconomic pathways (known as the Shared Socioeconomic Pathways), which is compatible with the climate change scenarios proposed by the Intergovernmental Panel on Climate Change (IPCC).

The new dataset has gone through several technical validation processes and proved its performance in accurately estimating urbanization levels. The comparison with previous datasets also showed that our updated dataset can capture the dynamics of urbanization levels more accurately than the previous ones.

Our projections can be used as an important input for other socioeconomic estimations, for example, population migration, urban land growth and economic changes, and ecological or environmental impact simulations such as biodiversity loss, carbon emissions, and air pollution. The projections can be visualized for each country and further aggregated for continental and global scales.

The projections under five scenarios and their uncertainties are publicly available in a tabular format on Figshare. The Python scripts for the projections are also provided.

Figure showing global urbanization dynamics under different shared socioeconomic pathways © Chen et al. (2022)
Global urbanization dynamics under different shared socioeconomic pathways

Further info:

Chen, S., Huang, Q., Muttarak, R., Fang, J., Liu, T., He, C., Liu, Z., & Zhu, L. (2022). Updating global urbanization projections under the Shared Socioeconomic Pathways. Scientific Data 9 (1) e137. DOI: 10.1038/s41597-022-01209-5 [pure.iiasa.ac.at/17960]

 

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.