Long-term, spatial urban land projections that simultaneously offer global coverage and local-scale
empirical accuracy are rare. Recently a set of such projections was produced using data-science-based
simulations and the Shared Socioeconomic Pathways (SSPs). these projections update at decadal time
intervals from 2000 to 2100 with a spatial resolution of 1/8 degree, while many socio-environmental
studies customarily run their analysis and modelling at finer spatial resolutions, e.g. 1-km. Here we
develop and validate an algorithm to downscale the 1/8-degree spatial urban land projections to the
1-km resolution. The algorithm uses an iterative process to allocate the decadal amount of urban land
expansion originally projected for each 1/8-degree grid to its constituent 1-km grids. The results are a
set of global maps showing urban land fractions at the 1-km resolution, updated at decadal intervals
from 2000 to 2100, under five different urban land expansion scenarios consistent with the SSPs. The
data can support studies of potential interactions between future urbanization and environmental
changes across spatial and temporal scales.
This dataset (Gao and Pesaresi, 2020) is downloadable at https://doi.org/10.7927/1z4r-ez63
GAO Jing;
PESARESI Martino;
2025-05-08
NATURE PORTFOLIO
JRC122243
2052-4463 (online),
https://doi.org/10.1038/s41597-021-01052-0,
https://publications.jrc.ec.europa.eu/repository/handle/JRC122243,
10.1038/s41597-021-01052-0 (online),
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