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High-resolution African population projections from radiative forcing and socio-economic models, 2000 to 2100.

Niklas Boke-OlénAbdulhakim M AbdiOla HallVeiko Lehsten
Published in: Scientific data (2017)
For its fifth assessment report, the Intergovernmental Panel on Climate Change divided future scenario projections (2005-2100) into two groups: Socio-Economic Pathways (SSPs) and Representative Concentration Pathways (RCPs). Each SSP has country-level urban and rural population projections, while the RCPs are based on radiative forcing caused by greenhouse gases, aerosols and associated land-use change. In order for these projections to be applicable in earth system models, SSP and RCP population projections must be at the same spatial scale. Thus, a gridded population dataset that takes into account both RCP-based urban fractions and SSP-based population projection is needed. To support this need, an annual (2000-2100) high resolution (approximately 1km at the equator) gridded population dataset conforming to both RCPs (urban land use) and SSPs (population) country level scenario data were created.
Keyphrases
  • high resolution
  • climate change
  • magnetic resonance
  • machine learning
  • risk assessment
  • big data
  • deep learning
  • electronic health record
  • current status
  • artificial intelligence