A cellular automata downscaling based 1 km global land use datasets (2010–2100)

Science Bulletin
By: , and 



Global climate and environmental change studies require detailed land-use and land-cover(LULC) information about the past, present, and future. In this paper, we discuss a methodology for downscaling coarse-resolution (i.e., half-degree) future land use scenarios to finer (i.e., 1 km) resolutions at the global scale using a grid-based spatially explicit cellular automata (CA) model. We account for spatial heterogeneity from topography, climate, soils, and socioeconomic variables. The model uses a global 30 m land cover map (2010) as the base input, a variety of biogeographic and socioeconomic variables, and an empirical analysis to downscale coarse-resolution land use information (specifically urban, crop and pasture). The output of this model offers the most current and finest-scale future LULC dynamics from 2010 to 2100 (with four representative concentration pathway (RCP) scenarios—RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) at a 1 km resolution within a globally consistent framework. The data are freely available for download, and will enable researchers to study the impacts of LULC change at the local scale.

Publication type Article
Publication Subtype Journal Article
Title A cellular automata downscaling based 1 km global land use datasets (2010–2100)
Series title Science Bulletin
DOI 10.1007/s11434-016-1148-1
Volume 61
Issue 21
Year Published 2016
Language English
Publisher Elsevier
Contributing office(s) Earth Resources Observation and Science (EROS) Center
Description 11 p.
First page 1651
Last page 1661
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