Estimation of gridded population and GDP scenarios with spatially explicit statistical downscaling

Daisuke Murakami, Yoshiki Yamagata

Research output: Contribution to journalArticlepeer-review

98 Citations (Scopus)


This study downscales the population and gross domestic product (GDP) scenarios given under Shared Socioeconomic Pathways (SSPs) into 0.5-degree grids. Our downscale approach has the following features. (i) It explicitly considers spatial and socioeconomic interactions among cities, (ii) it utilizes auxiliary variables, including road network and land cover, (iii) it endogenously estimates the influence from each factor by a model ensemble approach, and (iv) it allows us to control urban shrinkage/dispersion depending on SSPs. It is confirmed that our downscaling results are consistent with scenario assumptions (e.g., concentration in SSP1 and dispersion in SSP3). Besides, while existing grid-level scenarios tend to have overly-smoothed population distributions in nonurban areas, ours does not suffer from the problem, and captures the difference in urban and nonurban areas in a more reasonable manner. Our gridded dataset, including population counts and gross productivities by 0.5 degree grids by 10 years, are available from

Original languageEnglish
Article number2106
JournalSustainability (Switzerland)
Issue number7
Publication statusPublished - 2019
Externally publishedYes


  • Downscale
  • Ensemble learning
  • GDP
  • Population
  • Shared socioeconomic pathways
  • Spatial econometrics

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Renewable Energy, Sustainability and the Environment
  • Environmental Science (miscellaneous)
  • Energy Engineering and Power Technology
  • Management, Monitoring, Policy and Law


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