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Article: Simulation of urban land expansion in China at 30 m resolution through 2050 under shared socioeconomic pathways

TitleSimulation of urban land expansion in China at 30 m resolution through 2050 under shared socioeconomic pathways
Authors
Keywordscellular automata
China
scenario simulations
shared socioeconomic pathways
Tensor-FLUS
Urban expansion
Issue Date2022
Citation
GIScience and Remote Sensing, 2022, v. 59, n. 1, p. 1301-1320 How to Cite?
AbstractRapid urbanization has profoundly impacted social and environmental systems. China is the world’s largest developing country. Projecting future urban expansion in China is critical to alleviate any adverse impacts and achieve sustainable development goals. However, the existing national-scale urban expansion simulations at low or medium resolutions produce significant distortions in urban spatial patterns, limiting the utility of future projections. High-resolution simulation of urban expansion is challenging on a large scale owing to high computational demands. In this study, we used a high-performance cellular automata model (Tensor-FLUS) to simulate the urban expansion of China from 2015 to 2050, at 30 m spatial resolution, under shared socioeconomic pathways. The high-resolution (30 m) urban expansion simulations preserve greater spatial details and avoid 34.07–37.60% underestimation of the urban area, compared with simulation at 1 km resolution. The environmental impact assessments revealed that future urban expansion mainly encroaches on cropland (88.00–88.29%), with a greater likelihood of occupying productive cropland, placing substantial pressure on food production. Although the proportion of occupied natural land is relatively small (11.32–11.60%), newly expanded urban areas will tend to consume woodland and grassland of high ecological value, leading to profound impacts on the ecosystem. In general, the produced high-resolution future simulations can reduce the uncertainty of environmental impact assessment at the national scale. Furthermore, it can provide consistent projection data for research at the provincial or metropolitan scales to support urban planning and local climate change mitigation.
Persistent Identifierhttp://hdl.handle.net/10722/330842
ISSN
2023 Impact Factor: 6.0
2023 SCImago Journal Rankings: 1.756
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZhuang, Haoming-
dc.contributor.authorChen, Guangzhao-
dc.contributor.authorYan, Yuchao-
dc.contributor.authorLi, Bingjie-
dc.contributor.authorZeng, Li-
dc.contributor.authorOu, Jinpei-
dc.contributor.authorLiu, Kangyao-
dc.contributor.authorLiu, Xiaoping-
dc.date.accessioned2023-09-05T12:15:08Z-
dc.date.available2023-09-05T12:15:08Z-
dc.date.issued2022-
dc.identifier.citationGIScience and Remote Sensing, 2022, v. 59, n. 1, p. 1301-1320-
dc.identifier.issn1548-1603-
dc.identifier.urihttp://hdl.handle.net/10722/330842-
dc.description.abstractRapid urbanization has profoundly impacted social and environmental systems. China is the world’s largest developing country. Projecting future urban expansion in China is critical to alleviate any adverse impacts and achieve sustainable development goals. However, the existing national-scale urban expansion simulations at low or medium resolutions produce significant distortions in urban spatial patterns, limiting the utility of future projections. High-resolution simulation of urban expansion is challenging on a large scale owing to high computational demands. In this study, we used a high-performance cellular automata model (Tensor-FLUS) to simulate the urban expansion of China from 2015 to 2050, at 30 m spatial resolution, under shared socioeconomic pathways. The high-resolution (30 m) urban expansion simulations preserve greater spatial details and avoid 34.07–37.60% underestimation of the urban area, compared with simulation at 1 km resolution. The environmental impact assessments revealed that future urban expansion mainly encroaches on cropland (88.00–88.29%), with a greater likelihood of occupying productive cropland, placing substantial pressure on food production. Although the proportion of occupied natural land is relatively small (11.32–11.60%), newly expanded urban areas will tend to consume woodland and grassland of high ecological value, leading to profound impacts on the ecosystem. In general, the produced high-resolution future simulations can reduce the uncertainty of environmental impact assessment at the national scale. Furthermore, it can provide consistent projection data for research at the provincial or metropolitan scales to support urban planning and local climate change mitigation.-
dc.languageeng-
dc.relation.ispartofGIScience and Remote Sensing-
dc.subjectcellular automata-
dc.subjectChina-
dc.subjectscenario simulations-
dc.subjectshared socioeconomic pathways-
dc.subjectTensor-FLUS-
dc.subjectUrban expansion-
dc.titleSimulation of urban land expansion in China at 30 m resolution through 2050 under shared socioeconomic pathways-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/15481603.2022.2110197-
dc.identifier.scopuseid_2-s2.0-85136506034-
dc.identifier.volume59-
dc.identifier.issue1-
dc.identifier.spage1301-
dc.identifier.epage1320-
dc.identifier.isiWOS:000842825900001-

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