Urban expansion to 2030

“The Global Grid of Probabilities of Urban Expansion to 2030 presents spatially explicit probabilistic forecasts of global urban land cover change from 2000 to 2030 at a 2.5 arc-minute resolution. For each grid cell that is non-urban in 2000, a Monte-Carlo model assigned a probability of becoming urban by the year 2030.” – Socioeconomic Data and Applications Center (SEDAC)

Statistical concept and Methodology:

“The authors first extracted urban extent circa 2000 from the NASA MODIS Land Cover Type Product Version 5, which provides a conservative estimate of global urban land cover. The authors then used population densities from the Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) to create the population density driver map. They estimated the amount of new urban land in each United Nations region by 2030 in a Monte-Carlo fashion based on present empirical distribution of regional urban population densities and probability density functions of projected regional population and GDP values for 2030. To facilitate integration with other data products, CIESIN reprojected the data from Goode’s Homolosine to Geographic WGS84 projection.” – SEDAC

Population Expansion to 2030_2 (Custom) - Kopie


“Although regions were not excluded in the creation of these data some small urban areas, such as Tromso and Norilsk, are missing. This is a result of resampling the input land-cover data from 463 meters to 5 kilometers as described in the documentation.” – SEDAC

Data source:

Data Set:

Seto, K., B. Güneralp, and L.R. Hutyra. 2015. Global Grid of Probabilities of Urban Expansion to 2030. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://dx.doi.org/10.7927/H4Z899CG. Accessed 14 June 2016.

Scientific Publication:

Seto, K., B. Güneralp, and L.R. Hutyra. 2012. Global Forecasts of Urban Expansion to 2030 and Direct Impacts on Biodiversity and Carbon Pools. Proceedings of the National Academy of Sciences of the United States of America 109 (40): 16083-16088. http://dx.doi.org/10.1073/pnas.1211658109.

–> Crossite – for searching the DOI

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