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Management of urban land expansion in China through intensity assessment: A big data perspective
Zeng, Chen1,2; Yang, Ludi3; Dong, Jianing1
2017-06-01
Source PublicationJOURNAL OF CLEANER PRODUCTION
ISSN0959-6526
Volume153Issue:1Pages:637-647
Corresponding AuthorZeng, Chen()
AbstractRapid urbanization and widespread urban sprawl have induced a new era of urban resource management that focuses on efficiency, particularly in megacities in China. Big data is a platform for multi-source data fusion that helps to create spatially explicit decisions in regulating urban land expansion. In this study, we use big data to assess the intensity of urban land use in the metropolitan areas of China. OpenStreetMap and point-of-interest data are used to infer the urban function of each established parcel. Geographical weighted regression (GWR) is used to generate input output matchups and to formulate integrated urban land use intensity values. To incorporate spatial relations among cities into a final assessment, spatial networks derived from check-in data of the social media platform, "Weibo," are used to rank through the technique for order preference by similarity to the ideal solution (TOPSIS). Results show that Guangzhou has the most efficient urban land use system, followed by Shanghai and Shenzhen, and that Suzhou has the lowest urban land intensity. It is also revealed that the megalopolises in the Pearl River Delta and the Yangtze River Delta are superior in urban land use in general, whereas urban land use in the northern and western areas of China are less efficient. The megacities have strengths and weaknesses with respect to urban land use efficiency, and they advance at different stages when characteristic input output relationships are identified. This advancement is largely attributed to their unique political, economic, and cultural roles in China. Further improvements in each land use function will be proposed in the future and the profound networked big data from each city will be utilized to improve urban resource management. (C) 2016 Elsevier Ltd. All rights reserved.
KeywordUrban land expansion Urban land use intensity Big data GWR Megacities
DOI10.1016/j.jclepro.2016.11.090
WOS KeywordCARBON EMISSIONS ; URBANIZATION PROCESS ; TOPSIS METHOD ; RIVER DELTA ; CITY ; EFFICIENCY ; INSIGHTS ; JIANGSU ; REGION ; SCALE
Indexed BySCI
Language英语
Funding ProjectResearch Funds from China National Funds for Distinguished Young Scientists[71225005] ; Natural Science Foundation of China[41501179] ; Innovation Fund for Teachers from the Huazhong Agricultural University[2662015QC060] ; Innovation Fund for Teachers from the Huazhong Agricultural University[2662015PY166]
Funding OrganizationResearch Funds from China National Funds for Distinguished Young Scientists ; Natural Science Foundation of China ; Innovation Fund for Teachers from the Huazhong Agricultural University
WOS Research AreaEngineering ; Environmental Sciences & Ecology
WOS SubjectEngineering, Environmental ; Environmental Sciences
WOS IDWOS:000401042100058
PublisherELSEVIER SCI LTD
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Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/64501
Collection中国科学院地理科学与资源研究所
Corresponding AuthorZeng, Chen
Affiliation1.Huazhong Agr Univ, Dept Land Management, Wuhan 430070, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
3.Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China
Recommended Citation
GB/T 7714
Zeng, Chen,Yang, Ludi,Dong, Jianing. Management of urban land expansion in China through intensity assessment: A big data perspective[J]. JOURNAL OF CLEANER PRODUCTION,2017,153(1):637-647.
APA Zeng, Chen,Yang, Ludi,&Dong, Jianing.(2017).Management of urban land expansion in China through intensity assessment: A big data perspective.JOURNAL OF CLEANER PRODUCTION,153(1),637-647.
MLA Zeng, Chen,et al."Management of urban land expansion in China through intensity assessment: A big data perspective".JOURNAL OF CLEANER PRODUCTION 153.1(2017):637-647.
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