Management of urban land expansion in China through intensity assessment: A big data perspective
文献类型：期刊论文
| 作者 | Zeng, Chen1,2; Yang, Ludi3; Dong, Jianing1 |
| 刊名 | JOURNAL OF CLEANER PRODUCTION
 |
| 出版日期 | 2017-06-01 |
| 卷号 | 153期号:1页码:637-647 |
| 关键词 | Urban land expansion Urban land use intensity Big data GWR Megacities |
| ISSN号 | 0959-6526 |
| DOI | 10.1016/j.jclepro.2016.11.090 |
| 通讯作者 | Zeng, Chen() |
| 英文摘要 | Rapid 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. |
| WOS关键词 | CARBON EMISSIONS ; URBANIZATION PROCESS ; TOPSIS METHOD ; RIVER DELTA ; CITY ; EFFICIENCY ; INSIGHTS ; JIANGSU ; REGION ; SCALE |
| 资助项目 | Research 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] |
| WOS研究方向 | Engineering ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000401042100058 |
| 出版者 | ELSEVIER SCI LTD |
| 资助机构 | Research Funds from China National Funds for Distinguished Young Scientists ; Natural Science Foundation of China ; Innovation Fund for Teachers from the Huazhong Agricultural University |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/64500]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zeng, Chen |
| 作者单位 | 1.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 |
| 推荐引用方式 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. |
入库方式： OAI收割
来源：地理科学与资源研究所
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