4.7 Article

Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Shared Socioeconomic Pathways

Journal

EARTHS FUTURE
Volume 7, Issue 4, Pages 351-362

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2019EF001152

Keywords

urban area; urbanization; population; GDP; SDG; SSP

Funding

  1. U.S. Department of Energy, Office of Science, as part of research in Multi-Sector Dynamics, Earth and Environmental System Modeling Program
  2. NASA ROSES LULC Program [NNH11ZDA001N-LCLUC]
  3. NASA ROSES INCA Program [NNH14ZDA001N-INCA]
  4. Ministry of Environment of Korea through the Climate Change Correspondence Program [2004001300002]
  5. Korea Environmental Industry & Technology Institute (KEITI) [ARQ201403034006] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
  6. National Research Foundation of Korea [A0801014001] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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Improved understanding of the potential growth of urban areas at the national and global levels is needed for sustainable urban development. Current panel data analysis and local scale modeling are limited in projecting global urban area growth with large spatial heterogeneities. In this study, we developed country-specific urban area growth models using the time series data set of global urban extents (1992-2013) and projected the future growth of urban areas under five Shared Socioeconomic Pathways (SSPs). Our results indicate the global urban area would increase roughly 40-67% under five SSPs until 2050 relative to the base year of 2013, and this trend would continue to a growth ratio of more than 200% by 2100. The growth of urban areas under relatively unsustainable development pathways (e.g., regional rivalry SSP3 and inequality SSP4) is smaller compared to other SSPs. Although developing countries would remain as leading contributors to the increase of global urban areas in the future, they may exhibit different temporal patterns, that is, plateaued or monotonically increasing trends. This variation is primarily attributed to the compounding effect of the growth in population and gross domestic product. Our urban area data set presents a first country-level urban area projection under the five SSPs, spanning from 2013 to 2100. This data set has a great potential to support various global change studies, for example, urban sprawl simulation, integrated assessment modeling for sustainable development goals, and investigation of the impact of urbanization on atmospheric emissions, air quality, and human health.

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