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

TitleA cellular automata downscaling based 1 km global land use datasets (2010–2100)
Authors
KeywordsSpatial downscaling
LULC modeling
RCP scenarios
Urban expansion
Issue Date2016
Citation
Science Bulletin, 2016, v. 61, n. 21, p. 1651-1661 How to Cite?
Abstract© 2016, Science China Press and Springer-Verlag Berlin Heidelberg. 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.
Persistent Identifierhttp://hdl.handle.net/10722/296786
ISSN
2023 Impact Factor: 18.8
2023 SCImago Journal Rankings: 2.807
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, Xuecao-
dc.contributor.authorYu, Le-
dc.contributor.authorSohl, Terry-
dc.contributor.authorClinton, Nicholas-
dc.contributor.authorLi, Wenyu-
dc.contributor.authorZhu, Zhiliang-
dc.contributor.authorLiu, Xiaoping-
dc.contributor.authorGong, Peng-
dc.date.accessioned2021-02-25T15:16:40Z-
dc.date.available2021-02-25T15:16:40Z-
dc.date.issued2016-
dc.identifier.citationScience Bulletin, 2016, v. 61, n. 21, p. 1651-1661-
dc.identifier.issn2095-9273-
dc.identifier.urihttp://hdl.handle.net/10722/296786-
dc.description.abstract© 2016, Science China Press and Springer-Verlag Berlin Heidelberg. 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.-
dc.languageeng-
dc.relation.ispartofScience Bulletin-
dc.subjectSpatial downscaling-
dc.subjectLULC modeling-
dc.subjectRCP scenarios-
dc.subjectUrban expansion-
dc.titleA cellular automata downscaling based 1 km global land use datasets (2010–2100)-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s11434-016-1148-1-
dc.identifier.scopuseid_2-s2.0-84980454557-
dc.identifier.volume61-
dc.identifier.issue21-
dc.identifier.spage1651-
dc.identifier.epage1661-
dc.identifier.eissn2095-9281-
dc.identifier.isiWOS:000387414100004-
dc.identifier.issnl2095-9273-

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