Population and Environment

, Volume 28, Issue 2, pp 113–131

A SRES-based gridded global population dataset for 1990–2100

Original Paper

DOI: 10.1007/s11111-007-0035-8

Cite this article as:
Bengtsson, M., Shen, Y. & Oki, T. Popul Environ (2006) 28: 113. doi:10.1007/s11111-007-0035-8


Spatially explicit population data can play an important role in studies on environment and sustainability. Several gridded datasets on the present population exist, but global data on future populations are largely lacking. This paper presents a dataset covering three global population forecasts for the period 1990–2100 at 0.5-degrees resolution. The basis for these forecasts is the SRES scenarios developed for the IPCC climate-modeling framework. In addition, a gridded dataset of urban and rural populations for the period 1990–2050 is presented. To illustrate how the datasets can be used, future changes in population density and urbanization were analyzed for some of the world’s major river basins. This analysis shows that the population density in the Ganges basin, which is already very high, is likely to increase considerably. The highest future increase rates were found in some African and Middle-Eastern basins. The population dataset for 2015 was compared with one previously published gridded dataset. The comparison shows some differences in population density, mainly in small, highly urbanized coastal river basins, while for large basins, the two datasets agree fairly well. We hope that the datasets here presented will prove to be a useful resource also for other researchers of global environmental change and sustainable development.


Population density Urbanization Downscaling Sustainable development Water resources River basin SRES 

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Institute of Industrial ScienceThe University of TokyoTokyoJapan
  2. 2.Institute for Global Environmental Strategies (IGES)HayamaJapan
  3. 3.Center for Agricultural Resources Research (CARR), Chinese Academy of SciencesShijiazhuangChina

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